The unadjusted regression analysis for daily step count indicated a significant positive correlation with maximal daily WBGT and heat index (WBGT: estimate 974.4, SE 242.3; P <.001; heat index: estimate 317.6, SE 152.4; P =.04) with a low R 2 value (WBGT: R 2 =0.014; heat index: R 2 =0.003). On days without heavy rainfall, a similar positive yet nonsignificant correlation was observed for daily step count (estimate 1466.2, SE 852.9; P =.09; R 2 =0.002). The analysis for daily maximal temperature did not demonstrate any predictive power for step count ( R 2 =–0.001; estimate 87.54, SE 145.08; P =.55). After a logarithmic transformation of the dependent variable (step count) due to a funnel shape observed in residuals, the confounder-adjusted models revealed a significant positive relationship with the maximum WBGT (estimate 0.06, SE 0.02; P =.008; R 2 =0.248) (see Figure 4 for details). Other heat indicators showed positive yet nonsignificant associations with daily step count. Age and BMI emerged as significant predictors of daily step count ( P <.001).
For sleep duration in minutes, the linear regression model revealed a negative, however nonsignificant, correlation with minimal nighttime temperature and heat index at small P values, but with low predictive power (temperature: estimate –5.61, SE 3.24; P =.08, R 2 =0.002; heat index: estimate –4.77, SE 2.91; P =.10; R 2 =0.002). For minimal nighttime WBGT and sleep duration, simple linear regression had no explanatory power ( R 2 =–0.001, estimate –0.67, SE 2.98; P =.82). Similarly, the multiple linear regression analysis indicated that an increase in minimum nighttime temperatures and nightly minimal heat index corresponded with nonsignificant reductions in sleep duration, that is, by 5.56 minutes per °C increase ( P =.09; SE 3.234; R 2 =0.006) and 4.50 minutes per °C increase ( P =.12; SE 2.905; R 2 =0.006), respectively. We did not detect a significant relationship between nightly minimum WBGT and sleep duration (estimate 0.07 minutes; P =.98; SE 2.985; R 2 =0.003). Age proved to be a significant determinant of sleep duration across all models ( P =.03).
Unadjusted linear regression analysis of body shell temperature and minimal nighttime heat had no explanatory power giving their negative adjusted R 2 of –0.003 across all heat indicators (temperature: estimate 0.05, SE 0.07; P =.51; WBGT: estimate 0.05, SE 0.07; P =.51; heat index: estimate 0.04, SE 0.07; P =.53). The multiple linear regression models of nightly body shell temperature did not show significant results either, however at relatively high explanatory power, as indicated by their R 2 values (0.168, 0.170, and 0.170, respectively; temperature: estimate 0.03, SE 0.07; P =.63; WBGT: estimate 0.05, SE 0.07; P =.42; heat index: estimate 0.05, SE 0.06; P =.41, respectively). Gender ( P <.001) and BMI ( P =.04) were significant predictors in all 3 models.
The additional analysis incorporating the temporal confounder of weekday or weekend, detailed in Multimedia Appendix 5 , did not reveal any significant impact in the models. Regression models were not applied to heart rate measurements, as only the data sets of the 3 participants met the required 50% completeness. A summary of all the multiple regression models, including estimates, standard errors, P values, and other considered confounders for each health parameter and the associated extreme weather indicators is provided in Table 2 .
Health parameter, variable | Temperature | WBGT | Heat index | Precipitation <20 mm | ||||||||||||
Estimate (SE) | value | Estimate (SE) | value | Estimate (SE) | value | Estimate (SE) | value | |||||||||
Intercept | 10.47 (0.41) | <.001 | 9.26 (0.62) | <.001 | 10.12 (0.45) | <.001 | 10.79 (0.16) | <.001 | ||||||||
Gender (men) | 0.06 (0.05) | .25 | 0.05 (0.05) | .28 | 0.06 (0.05) | .27 | 0.06 (0.05) | .25 | ||||||||
Age | –0.02 (0.00) | <.001 | –0.02 (0.00) | <.001 | –0.02 (0.00) | <.001 | –0.02 (0.00) | <.001 | ||||||||
Maximal daily weather measurement | 0.01 (0.01) | .33 | 0.06 (0.02) | .008 | 0.03 (0.01) | .08 | 0.07 (0.08) | .36 | ||||||||
BMI | –0.03 (0.01) | <.001 | –0.03 (0.01) | <.001 | –0.03 (0.01) | <.001 | –0.03 (0.01) | <.001 | ||||||||
Intercept | 537.52 (58.98) | <.001 | 438.98 (52.84) | <.001 | 520.52 (54.42) | <.001 | — | — | ||||||||
Gender (men) | 1.42 (6.01) | .81 | 0.93 (6.01) | .88 | 1.32 (6.01) | .83 | — | — | ||||||||
Age | –0.39 (0.17) | .03 | –0.38 (0.18) | .03 | –0.38 (0.17) | .03 | — | — | ||||||||
Minimal nightly weather measurement | –5.56 (3.23) | .09 | 0.07 (2.99) | .98 | –4.50 (2.91) | .12 | — | — | ||||||||
BMI | 1.02 (0.61) | .09 | 1.03 (0.61) | .09 | 1.00 (0.61) | .10 | — | — | ||||||||
Intercept | 36.31 (1.34) | <.001 | 35.98 (1.25) | <.001 | 36.02 (1.19) | <.001 | — | — | ||||||||
Gender (men) | –0.72 (0.12) | <.001 | –0.72 (0.12) | <.001 | –0.72 (0.12) | <.001 | — | — | ||||||||
Minimum nightly weather measurement | 0.03 (0.07) | .63 | 0.05 (0.07) | .42 | 0.05 (0.06) | .41 | — | — | ||||||||
Age | 0.00 (0.01) | .41 | 0.00 (0.01) | .44 | 0.00 (0.01) | .40 | — | — | ||||||||
BMI | –0.03 (0.02) | .04 | –0.03 (0.02) | .04 | –0.04 (0.02) | .04 | — | — |
a This is a logarithmically transformed model for step count and standard models for sleep duration and body temperature. The table includes estimates, standard errors, and P values for each health parameter—sleep duration, step count, and body temperature—along with their associated extreme weather indicators. Health parameters were included of adult participants having at least 50% data completeness for the respective health parameter. Depending on the model, the weather indicators considered were temperature, heat index, wet bulb globe temperature, and precipitation. Additionally, the multiple linear regression models incorporated gender, age, and BMI, as the data validity analysis demonstrated the significance of these confounders.
b WBGT: wet bulb globe temperature.
c Not available.
The findings of our study highlight the advantages and challenges associated with the use of wearable devices for the continuous monitoring of vital signs in rural sub-Saharan populations. We found using wearables a pertinent approach for understanding individual impacts of weather exposures. Our research emphasizes the feasibility and effectiveness of integrating wearable technology into health research, in particular, to understand individual exposures and activity patterns such as daily steps and sleep duration. We identified a correlation between weather exposures and various health metrics. Notably, there is a positive relationship between daily step count and the maximum WBGT as well as a potential negative association between nighttime temperatures and sleep duration. These findings contribute to our understanding of the possible health impacts of climate change, with a particular focus on rural regions in western Kenya.
Our study shows environmental exposures such as frequent heavy rainfall and extreme heat, with approximately 20.7% (4044/19,576) of our weather station readings surpassing the heat index caution threshold [ 13 ]—a pattern consistent with WBGT findings. We found a strong positive correlation between daily step count and maximum WBGT across both models. Additionally, a positive relationship with the heat index was observed in the unadjusted model. Although many studies indicate a negative link between heat and physical activity [ 30 ], the relationship between temperature and activity levels remains inconsistent. This discrepancy necessitates further investigation. For instance, a study [ 34 ] conducted in Qatar utilizing wearable pedometers discovered negative correlations between daily step count and both precipitation and temperature. However, that study reported varying associations with WBGT depending on the analytical model employed. Our findings emphasize the need for deeper investigation into this relationship [ 4 ]. External factors such as seasonal farming activities illustrated in Figure 4 or specific mitigation practices might significantly influence this correlation and therefore merit additional investigation [ 17 ], especially given the scarcity of objectively generated data on activity levels and physical activity profiles in rural sub-Saharan African populations [ 35 ].
In our study, we observed a negative trend between minimum nighttime temperature and sleep duration as well as between the minimal nighttime heat index and sleep duration, but these relationships were not statistically significant in either model. However, this trend aligns with previous research that has linked warmer nights to shorter sleep durations, suggesting that climate change could significantly affect sleep health [ 4 , 8 , 32 ]. For example, a comprehensive study by Minor et al [ 8 ] utilizing sleep data of 47,628 participants across 68 countries found a correlation between shorter sleep duration and warmer nights. In line with these findings, all studies in the scoping review of Koch et al [ 4 ] reported a negative correlation between sleep duration and heat. These studies underscore the risk of insufficient sleep, in light of the expected impact of global warming due to climate change on local heat exposure [ 8 ]. The review of Caddick et al [ 36 ] suggests that optimal ambient temperatures for sleep lie between 17 °C and 28 °C, with 40%-60% humidity, although this may vary based on other factors. Insufficient sleep, whether due to short duration or disruptions, can negatively affect human health, potentially compromising the immune system [ 37 ] and increasing cardiovascular risk [ 38 ].
Regarding body shell temperature, our study did not find significant associations with average nightly body shell temperature and heat. However, previous studies [ 4 , 31 ] have suggested a possible connection. In our analysis, gender and age emerged as critical factors in all 3 models, emphasizing the importance of demographic and physiological factors in body temperature regulation. The inconclusive results in our study might be attributed to the limited sample size and issues with data integrity. Furthermore, natural thermoregulatory processes such as evaporation and the thermoregulatory behaviors of participants should be considered when evaluating body shell temperature [ 24 ].
Our study shows improved data completeness compared to previous research in Burkina Faso [ 15 ] and the United States [ 27 ], especially in thermometer patch data, likely due to enhanced adhesion using medical tape [ 15 ]. However, heart rate data showed lower completeness, which may have been affected by technical factors such as the proximity of the sensors to the skin, the impact of motion, and potential device errors. Similar studies using certain wearable devices reported data loss due to wearable malfunctions such as connection issues [ 39 ]. Other factors such as blood vessel thickness, skin thickness, obesity, and age might also affect measurement quality and completeness, potentially explaining the gender-specific differences observed in our data, where factors such as thinner skin in women or older populations or thicker blood vessels in men could enhance photoplethysmography signals [ 40 , 41 ]. Other factors that have been mentioned in the scientific literature are the skin pigmentations of the participants; several studies have noted a correlation between the Fitz-Patrick skin scale and heart rate measurements via photoplethysmography, suggesting reduced heart rate measurement accuracy in individuals with higher Fitz-Patrick scale values [ 40 , 42 ], although some studies [ 43 ] did not find this correlation. To mitigate this, wearables are starting to implement enhanced photoplethysmography sensors or infrared measurements [ 42 ]. Moreover, gender may present contradictory effects on the data collection [ 40 ]. The influence of BMI on signal quality remains uncertain [ 40 ], with additional variables such as blood vessel dilation during physical activity also playing a role [ 40 ]. Participant adherence challenges were also observed, as some felt uncomfortable wearing the device continuously, especially at night.
Our research aligns with previous studies on average daily activity and sleep duration, particularly regarding the influence of age [ 15 , 32 , 34 ]. Although body shell temperature readings aligned with physiological norms, indicating their usefulness in identifying individual anomalies [ 24 ], they were notably low, suggesting potential nighttime evaporation processes [ 24 ]. As with prior research, factors such as gender and BMI affected body shell temperature [ 4 , 24 ], necessitating further research to comprehensively grasp temperature impacts.
The internal validity of the wearables used in this study was not evaluated; however, models older than the WPHR used here, some requiring manual sleep initiation, have shown largely satisfactory results. Gruwez et al [ 44 ] identified a significant correlation between Withings wearables and a research-grade actigraph for step count during daily activities. However, a review by Fuller et al [ 45 ] revealed an underestimation of step count in Withings wearables in most examined studies. Comparisons of Withings wearables to polysomnography revealed no significant differences in sleep duration measurements [ 39 ], and various studies have noted consistent correlations with polysomnography-recorded total sleep duration [ 39 , 44 ]. Regulatory constraints restricted the recruitment of younger participants in our study, affecting its generalizability. Furthermore, smartphone usage restrictions in Kenyan boarding schools, especially pertinent to the substantial under-15 years demographic, could pose challenges for future research [ 17 ]. In addition, as explained in the methods section, only the data sets of the adult participants were analyzed with regard to weather effects. Our study has other limitations such as uncorrected multiple testing and potential influences of the COVID-19 pandemic on data. In Kenya, the COVID-19 pandemic caused governmental restrictions on public life such as nighttime curfew until October 20, 2021, which affected 22 (26.5%) participants during their study participation—likely influencing the data collected [ 46 ]. Research during the 2020 COVID lockdowns reported reduced total sleep duration and increased napping [ 47 ], and a South African study observed decreased mobility, particularly on weekends [ 48 ]. Future research should consider a wider range of variables, account for the carryover effects of prior day heat strain [ 49 ], and address technical challenges such as inaccessible raw data, software issues, high data missingness for heart rate due to factors such as skin type [ 40 ], and possible algorithmic biases. Our study does not account for factors such as clothing, air circulation, bedding, and individual differences such as gender, which can influence the relationship between heat and sleep duration [ 36 ].
Our study shows the potential of wearable devices to monitor vital signs and assess the impact of environmental exposures on health in rural sub-Saharan settings, with implications for understanding the nuanced effects of climate change. Despite a robust data set, our findings indicate the need for improved wearable technology to ensure data completeness across diverse demographic groups, acknowledging the impact of factors such as age, gender, and BMI. The positive correlation between physical activity levels and high WBGT offers new insights into behavior during extreme weather conditions, while the nonsignificant trends in sleep duration in relation to temperature call for further investigation. These observations are crucial for public health strategies in climate-vulnerable regions, guiding the integration of wearables in longitudinal health monitoring and climate resilience research. Future studies should expand on the relationship between weather and health outcomes, including a broader demographic and addressing technical challenges identified in wearable data collection. This research contributes to a growing body of knowledge that will inform both technological innovation in health monitoring and the development of interventions to mitigate the health impacts of global climate dynamics.
We thank the German Research Foundation (Deutsche Forschungsgemeinschaft) for supporting this work as part of a Deutsche Forschungsgemeinschaft–funded research unit (Forschungsgruppe FOR 2936/project: 409670289). We acknowledge the support of Else Kröner-Fresenius-Stiftung from the Heidelberg Graduate School of Global Health. For the publication fee we acknowledge financial support by Heidelberg University and by the Else Kröner-Fresenius-Stiftung within the Heidelberg Graduate School of Global Health. The funders had no influence on the design, data collection and analysis, the decision to publish or the preparation of the manuscript. During the preparation of this work, the author(s) used ChatGPT in order to improve language and readability of this manuscript. After using this tool/service, the authors reviewed and edited the content as needed and take full responsibility for the content of the publication.
Deidentified wearable data, weather data, and R scripts will be available for scientific purposes with publication on reasonable request to the corresponding author SB ([email protected]).
SB, TB, and SM planned this study and led its implementation. SM, DO, DK, JOM, COO, and IM conducted and supervised the study on site, remotely advised by SB and IM. SH, MK, MAM, SB, and IM assessed the data and performed the data analysis. IM analyzed the data, supervised and verified by SB. All authors critically and freely contributed to the final draft and confirmed the publication.
None declared.
Detailed technical information on the wearables used.
Additional information on data analysis.
Added variables and residual plots of regression models.
Detailed results on data completeness and data validity.
Additional regression models incorporating weekday or weekend.
ChatGPT conversation.
Health and Demographic Surveillance System |
low- and middle-income countries |
Mann-Whitney U test |
Strengthening the Reporting of Observational Studies in Epidemiology |
wet bulb globe temperature |
Withings pulse heart rate |
Edited by G Eysenbach, L Buis; submitted 18.11.23; peer-reviewed by H Aghayan Golkashani; comments to author 22.12.23; revised version received 16.01.24; accepted 26.01.24; published 04.07.24.
©Ina Matzke, Sophie Huhn, Mara Koch, Martina Anna Maggioni, Stephen Munga, Julius Okoth Muma, Collins Ochieng Odhiambo, Daniel Kwaro, David Obor, Till Bärnighausen, Peter Dambach, Sandra Barteit. Originally published in JMIR mHealth and uHealth (https://mhealth.jmir.org), 04.07.2024.
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Spatiotemporal variations of vegetation and its response to climate change and human activities in arid areas—a case study of the shule river basin, northwestern china.
2. materials and methods, 2.1. study area, 2.2. datasets, 2.2.1. vegetation, 2.2.2. land cover, 2.2.3. precipitation, 2.2.4. land surface temperature, 2.2.5. surface water area, 2.2.6. dem and road, 2.3. methods, 2.3.1. retrieval of fvc time series data, 2.3.2. vegetation trend analysis, 2.3.3. partial correlation analysis, 2.3.4. calculating contribution of driving factors to variation in fvc, 3.1. temporal change of vegetation, 3.2. spatial pattern of vegetation dynamics, 3.3. correlations between climate factors and fvc, 4. discussion, 4.1. contributions of climate change and human activities to vegetation dynamics, 4.2. land cover dynamics and their response to climate change and human activities, 5. conclusions, author contributions, data availability statement, conflicts of interest.
Click here to enlarge figure
Year | Minimum | Maximum | NDVI (0.5%) | NDVI (99.5%) |
---|---|---|---|---|
2000 | −0.488 | 0.905 | 0.004 | 0.659 |
2001 | −0.141 | 0.491 | 0.000 | 0.327 |
2002 | −0.137 | 0.531 | 0.002 | 0.371 |
2003 | −0.482 | 0.993 | 0.004 | 0.600 |
2004 | −0.083 | 0.550 | 0.001 | 0.378 |
2005 | −0.385 | 0.541 | 0.000 | 0.356 |
2006 | −0.135 | 0.696 | 0.002 | 0.412 |
2007 | −0.365 | 0.543 | 0.002 | 0.365 |
2008 | −0.379 | 0.561 | 0.000 | 0.373 |
2009 | −0.153 | 0.554 | 0.002 | 0.363 |
2010 | −0.087 | 0.552 | 0.000 | 0.397 |
2011 | −0.163 | 0.554 | 0.003 | 0.416 |
2012 | −0.087 | 0.662 | 0.004 | 0.433 |
2013 | −0.085 | 0.691 | 0.015 | 0.521 |
2014 | −0.048 | 0.669 | 0.017 | 0.520 |
2015 | 0.001 | 0.686 | 0.017 | 0.516 |
2016 | −0.009 | 0.680 | 0.015 | 0.501 |
2017 | −0.055 | 0.680 | 0.015 | 0.507 |
2018 | −0.035 | 0.677 | 0.018 | 0.520 |
2019 | −0.106 | 0.671 | 0.016 | 0.513 |
Trend of FVC | p | Slope | Area (%) | |||
---|---|---|---|---|---|---|
2000–2004 | 2005–2009 | 2010–2014 | 2015–2019 | |||
Significantly increased | p < 0.05 | slope ≥ 0.01 | 0.20 | 0.38 | 0.89 | 0.68 |
Significantly decreased | p < 0.05 | slope ≤ −0.01 | 0.29 | 0.21 | 0.32 | 0.25 |
Significantly stable | p < 0.05 | −0.01 < slope < 0.01 | 46.75 | 46.59 | 48.18 | 46.65 |
Non-significant change | p ≥ 0.05 | - | 52.76 | 52.82 | 50.61 | 52.42 |
V | Precipitation | LST | Area of Surface Water | |
---|---|---|---|---|
V | 1 | 0.575 | −0.107 | 0.744 |
Precipitation | 0.575 | 1 | −0.136 | 0.548 |
LST | −0.107 | −0.136 | 0 | 0.030 |
Area of surface water | 0.744 | 0.548 | 0.030 | 0 |
2000–2004 | 2005–2009 | 2010–2014 | 2015–2019 | |
---|---|---|---|---|
The contribution of climate change | 17.47% | 25.48% | 28.31% | 30.81% |
The contribution of human activities | 24.14% | 30.45% | 25.69% | 26.80% |
Land Cover Types | FVC (%) | |||||||||
---|---|---|---|---|---|---|---|---|---|---|
[0, 0.1] | (0.1, 0.2] | (0.2, 0.3] | (0.3, 0.4] | (0.4, 0.5] | (0.5, 0.6] | (0.6, 0.7] | (0.7, 0.8] | (0.8, 0.9] | (0.9, 1.0] | |
Cropland | 0.01 | 3.32 | 19.03 | 31.73 | 46.81 | 56.59 | 68.38 | 79.62 | 83.80 | 83.47 |
Grassland | 0.45 | 28.61 | 41.77 | 38.87 | 32.75 | 31.51 | 26.88 | 13.58 | 14.08 | 13.70 |
Sparse vegetation | 8.05 | 23.67 | 23.30 | 11.32 | 6.59 | 2.25 | 1.19 | 1.89 | 0.00 | 0.47 |
Wetlands | 0.17 | 0.81 | 10.60 | 15.87 | 10.77 | 4.18 | 1.19 | 1.13 | 1.76 | 0.00 |
Impervious surfaces | 0.01 | 0.36 | 0.63 | 1.48 | 1.54 | 5.47 | 1.98 | 3.77 | 0.35 | 1.06 |
Bare areas | 91.31 | 43.23 | 4.67 | 0.74 | 1.54 | 0.00 | 0.40 | 0.00 | 0.00 | 1.30 |
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He, X.; Zhang, L.; Lu, Y.; Chai, L. Spatiotemporal Variations of Vegetation and Its Response to Climate Change and Human Activities in Arid Areas—A Case Study of the Shule River Basin, Northwestern China. Forests 2024 , 15 , 1147. https://doi.org/10.3390/f15071147
He X, Zhang L, Lu Y, Chai L. Spatiotemporal Variations of Vegetation and Its Response to Climate Change and Human Activities in Arid Areas—A Case Study of the Shule River Basin, Northwestern China. Forests . 2024; 15(7):1147. https://doi.org/10.3390/f15071147
He, Xiaorui, Luqing Zhang, Yuehan Lu, and Linghuan Chai. 2024. "Spatiotemporal Variations of Vegetation and Its Response to Climate Change and Human Activities in Arid Areas—A Case Study of the Shule River Basin, Northwestern China" Forests 15, no. 7: 1147. https://doi.org/10.3390/f15071147
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Published: March 08, 2023
Putting together a compelling case study is one of the most powerful strategies for showcasing your product and attracting future customers. But it's not easy to create case studies that your audience can’t wait to read.
In this post, we’ll go over the definition of a case study and the best examples to inspire you.
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There’s no better way to generate more leads than by writing case studies . But without case study examples to draw inspiration from, it can be difficult to write impactful studies that convince visitors to submit a form.
To help you create an attractive and high-converting case study, we've put together a list of some of our favorites. This list includes famous case studies in marketing, technology, and business.
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These marketing case studies with solutions show the value proposition of each product. They also show how each company benefited in both the short and long term using quantitative data. In other words, you don’t get just nice statements, like "This company helped us a lot." You see actual change within the firm through numbers and figures.
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The sparse copy and prominent headings show that you don’t need a lot of elaborate information to show the value of your products and services. Like the other case study examples on this list, it includes visuals and quotes to demonstrate the effectiveness of the company’s efforts. The case study ends with a bulleted list that shows the results.
If you’ve worked with a company that’s well-known, use only the name in the title — like Carol H. Williams, one of the nation’s top advertising agencies, does here. The "DTU," stands for "Discover the Unexpected." It generates interest because you want to find out what the initials mean.
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Further down the page, they use icons like a heart and a circle to illustrate their pitch angles, and graphs to showcase their results. Rather than writing which publications have mentioned Porch.com during Fractl’s campaign, they incorporated the media outlets’ icons for further visual diversity.
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Each section is simple, showing a single piece of the new website's interface so that users aren’t overwhelmed with information and can focus on what matters most.
If you're more interested in text, you can read the objective for each feature. Fantasy understands that, as a potential customer, this is all you need to know. Scrolling further, you're greeted with a simple "Contact Us" CTA.
If your client had a lot of positive things to say about you, take a note from App Annie’s Rovio case study and open up with a quote from your client. The case study also closes with a quote, so that the case study doesn’t seem like a promotion written by your marketing team but a story that’s taken straight from your client’s mouth. It includes a photo of a Rovio employee, too.
Another thing this example does well? It immediately includes a link to the product that Rovio used (namely, App Annie Intelligence) at the top of the case study. The case study closes with a call-to-action button prompting users to book a demo.
Google takes a different approach to text-focused case studies by choosing three different companies to highlight.
The case study is clean and easily scannable. It has sections for each company, with quotes and headers that clarify the way these three distinct stories connect. The simple format also uses colors and text that align with the Google brand.
Another differentiator is the focus on data. This case study is less than a thousand words, but it's packed with useful data points. Data-driven insights quickly and clearly show how the value of leveraging first-party data while prioritizing consumer privacy.
Switch is an international marketing agency based in Malta that knocks it out of the park with this case study. Its biggest challenge is effectively communicating what it did for its client without ever revealing the client’s name. It also effectively keeps non-marketers in the loop by including a glossary of terms on page 4.
The PDF case study reads like a compelling research article, including titles like "In-Depth Performance Marketing Case Study," "Scenario," and "Approach," so that readers get a high-level overview of what the client needed and why they approached Switch. It also includes a different page for each strategy. For instance, if you’d only be interested in hiring Switch for optimizing your Facebook ads, you can skip to page 10 to see how they did it.
The PDF is fourteen pages long but features big fonts and plenty of white space, so viewers can easily skim it in only a few minutes.
Let pictures speak for you, like OH Partners did in this case study. While you’ll quickly come across a heading and some text when you land on this case study page, you’ll get the bulk of the case study through examples of actual work OH Partners did for its client. You will see OH Partners’ work in a billboard, magazine, and video. This communicates to website visitors that if they work with OH Partners, their business will be visible everywhere.
And like the other case studies here, it closes with a summary of what the firm achieved for its client in an eye-catching way.
Digitas' case study page for Sprite’s #ILOVEYOUHATER campaign keeps it brief while communicating the key facts of Digitas’ work for the popular soda brand. The page opens with an impactful image of a hundred people facing a single man. It turns out, that man is the biggest "bully" in Argentina, and the people facing him are those whom he’s bullied before.
Scrolling down, it's obvious that Digitas kept Sprite at the forefront of their strategy, but more than that, they used real people as their focal point. They leveraged the Twitter API to pull data from Tweets that people had actually tweeted to find the identity of the biggest "hater" in the country. That turned out to be @AguanteElCofler, a Twitter user who has since been suspended.
HermanMiller sells sleek, utilitarian furniture with no frills and extreme functionality, and that ethos extends to its case study page for a hospital in Dubai.
What first attracted me to this case study was the beautiful video at the top and the clean user experience. User experience matters a lot in a case study. It determines whether users will keep reading or leave. Another notable aspect of this case study is that the video includes closed-captioning for greater accessibility, and users have the option of expanding the CC and searching through the text.
HermanMiller’s case study also offers an impressive amount of information packed in just a few short paragraphs for those wanting to understand the nuances of their strategy. It closes out with a quote from their client and, most importantly, the list of furniture products that the hospital purchased from the brand.
Do you work continuously with your clients? Consider structuring your case study page like Amazon did in this stellar case study example. Instead of just featuring one article about Capital One and how it benefited from using AWS, Amazon features a series of articles that you can then access if you’re interested in reading more. It goes all the way back to 2016, all with different stories that feature Capital One’s achievements using AWS.
This may look unattainable for a small firm, but you don’t have to go to extreme measures and do it for every single one of your clients. You could choose the one you most wish to focus on and establish a contact both on your side and your client’s for coming up with the content. Check in every year and write a new piece. These don’t have to be long, either — five hundred to eight hundred words will do.
While Asana's case study design looks text-heavy, there's a good reason. It reads like a creative story, told entirely from the customer's perspective.
For instance, Asana knows you won't trust its word alone on why this product is useful. So, they let Tony Phillips, HackReactor CEO, tell you instead: "We take in a lot of information. Our brains are awful at storage but very good at thinking; you really start to want some third party to store your information so you can do something with it."
Asana features frequent quotes from Phillips to break up the wall of text and humanize the case study. It reads like an in-depth interview and captivates the reader through creative storytelling. Even more, Asana includes in-depth detail about how HackReactor uses Asana. This includes how they build templates and workflows:
"There's a huge differentiator between Asana and other tools, and that’s the very easy API access. Even if Asana isn’t the perfect fit for a workflow, someone like me— a relatively mediocre software engineer—can add functionality via the API to build a custom solution that helps a team get more done."
Amp Agency's Patagonia marketing strategy aimed to appeal to a new audience through guerrilla marketing efforts and a coast-to-coast road trip. Their case study page effectively conveys a voyager theme, complete with real photos of Patagonia customers from across the U.S., and a map of the expedition. I liked Amp Agency's storytelling approach best. It captures viewers' attention from start to finish simply because it's an intriguing and unique approach to marketing.
Evisort opens up its NetApp case study with an at-a-glance overview of the client. It’s imperative to always focus on the client in your case study — not on your amazing product and equally amazing team. By opening up with a snapshot of the client’s company, Evisort places the focus on the client.
This case study example checks all the boxes for a great case study that’s informative, thorough, and compelling. It includes quotes from the client and details about the challenges NetApp faced during the COVID pandemic. It closes out with a quote from the client and with a link to download the case study in PDF format, which is incredibly important if you want your case study to be accessible in a wider variety of formats.
Including highly specialized information in your case study is an effective way to show prospects that you’re not just trying to get their business. You’re deep within their industry, too, and willing to learn everything you need to learn to create a solution that works specifically for them.
Cloudflight does a splendid job at that in its Copernicus Land Monitoring case study. While the information may be difficult to read at first glance, it will capture the interest of prospects who are in the environmental industry. It thus shows Cloudflight’s value as a partner much more effectively than a general case study would.
The page is comprehensive and ends with a compelling call-to-action — "Looking for a solution that automates, and enhances your Big Data system? Are you struggling with large datasets and accessibility? We would be happy to advise and support you!" The clean, whitespace-heavy page is an effective example of using a case study to capture future leads.
If you’re targeting large enterprises with a long purchasing cycle, you’ll want to include a wealth of information in an easily transferable format. That’s what Textel does here in its PDF case study for Valvoline. It greets the user with an eye-catching headline that shows the value of using Textel. Valvoline saw a significant return on investment from using the platform.
Another smart decision in this case study is highlighting the client’s quote by putting it in green font and doing the same thing for the client’s results because it helps the reader quickly connect the two pieces of information. If you’re in a hurry, you can also take a look at the "At a Glance" column to get the key facts of the case study, starting with information about Valvoline.
In this blog-post-like case study, Happeo opens with a quote from the client, then dives into a compelling heading: "Technology at the forefront of Hunt Club's strategy." Say you’re investigating Happeo as a solution and consider your firm to be technology-driven. This approach would spark your curiosity about why the client chose to work with Happeo. It also effectively communicates the software’s value proposition without sounding like it’s coming from an in-house marketing team.
Every paragraph is a quote written from the customer’s perspective. Later down the page, the case study also dives into "the features that changed the game for Hunt Club," giving Happeo a chance to highlight some of the platform’s most salient features.
What's great about CTP's case study page for their Red Sox Season Campaign is their combination of video, images, and text. A video automatically begins playing when you visit the page, and as you scroll, you'll see more embedded videos of Red Sox players, a compilation of print ads, and social media images you can click to enlarge.
At the bottom, it says "Find out how we can do something similar for your brand." The page is clean, cohesive, and aesthetically pleasing. It invites viewers to appreciate the well-roundedness of CTP's campaign for Boston's beloved baseball team.
Sometimes, simple is key. Genuine's case study for Acoustic is straightforward and minimal, with just a few short paragraphs, including "Reimagining the B2B website experience," "Speaking to marketers 1:1," and "Inventing Together." After the core of the case study, we then see a quote from Acoustic’s CMO and the results Genuine achieved for the company.
The simplicity of the page allows the reader to focus on both the visual aspects and the copy. The page displays Genuine's brand personality while offering the viewer all the necessary information they need.
Apptio’s case study for Wargaming summarizes three key pieces of information right at the beginning: The goals, the obstacles, and the results.
Readers then have the opportunity to continue reading — or they can walk away right then with the information they need. This case study also excels in keeping the human interest factor by formatting the information like an interview.
The piece is well-organized and uses compelling headers to keep the reader engaged. Despite its length, Apptio's case study is appealing enough to keep the viewer's attention. Every Apptio case study ends with a "recommendation for other companies" section, where the client can give advice for other companies that are looking for a similar solution but aren’t sure how to get started.
Zendesk's Airbnb case study reads like a blog post, and focuses equally on Zendesk and Airbnb, highlighting a true partnership between the companies. To captivate readers, it begins like this: "Halfway around the globe is a place to stay with your name on it. At least for a weekend."
The piece focuses on telling a good story and provides photographs of beautiful Airbnb locations. In a case study meant to highlight Zendesk's helpfulness, nothing could be more authentic than their decision to focus on Airbnb's service in such great detail.
Like some of the other top examples in this list, Biobot opens its case study with a quote from its client, which captures the value proposition of working with Biobot. It mentions the COVID pandemic and goes into detail about the challenges the client faced during this time.
This case study is structured more like a news article than a traditional case study. This format can work in more formal industries where decision-makers need to see in-depth information about the case. Be sure to test different methods and measure engagement .
You don't always need a ton of text or a video to convey your message — sometimes, you just need a few paragraphs and bullet points. Gartner does a fantastic job of quickly providing the fundamental statistics a potential customer would need to know, without boggling down their readers with dense paragraphs. The case study closes with a shaded box that summarizes the impact that Gartner had on its client. It includes a quote and a call-to-action to "Learn More."
This case study example by Redapt is another great demonstration of the power of summarizing your case study’s takeaways right at the start of the study. Redapt includes three easy-to-scan columns: "The problem," "the solution," and "the outcome." But its most notable feature is a section titled "Moment of clarity," which shows why this particular project was difficult or challenging.
The section is shaded in green, making it impossible to miss. Redapt does the same thing for each case study. In the same way, you should highlight the "turning point" for both you and your client when you were working toward a solution.
Convoso’s PDF case study for Digital Market Media immediately mentions the results that the client achieved and takes advantage of white space. On the second page, the case study presents more influential results. It’s colorful and engaging and closes with a spread that prompts readers to request a demo.
Ericsson’s case study page for Orange Spain is an excellent example of using diverse written and visual media — such as videos, graphs, and quotes — to showcase the success a client experienced. Throughout the case study, Ericsson provides links to product and service pages users might find relevant as they’re reading the study.
For instance, under the heading "Preloaded with the power of automation," Ericsson mentions its Ericsson Operations Engine product, then links to that product page. It closes the case study with a link to another product page.
Now that you've got a great list of examples of case studies, think about a topic you'd like to write about that highlights your company or work you did with a customer.
A customer’s success story is the most persuasive marketing material you could ever create. With a strong portfolio of case studies, you can ensure prospects know why they should give you their business.
Editor's note: This post was originally published in August 2018 and has been updated for comprehensiveness.
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The reports to the Vaccine Adverse Event Reporting System met the case definition of myocarditis (reported cases). Among individuals older than 40 years of age, there were no more than 8 reports of myocarditis for any individual age after receiving either vaccine. For the BNT162b2 vaccine, there were 114 246 837 first vaccination doses and 95 532 396 second vaccination doses; and for the mRNA-1273 vaccine, there were 78 158 611 and 66 163 001, respectively. The y-axis range differs between panels A and B.
The reports to the Vaccine Adverse Event Reporting System met the case definition of myocarditis (reported cases). Among recipients of either vaccine, there were only 13 reports or less of myocarditis beyond 10 days for any individual time from vaccination to symptom onset. The y-axis range differs between panels A and B.
A, For the BNT162b2 vaccine, there were 138 reported cases of myocarditis with known date for symptom onset and dose after 114 246 837 first vaccination doses and 888 reported cases after 95 532 396 second vaccination doses.
B, For the mRNA-1273 vaccine, there were 116 reported cases of myocarditis with known date for symptom onset and dose after 78 158 611 first vaccination doses and 311 reported cases after 66 163 001 second vaccination doses.
eMethods. Medical Dictionary for Regulatory Activities Preferred Terms, Definitions of Myocarditis and Pericarditis, Myocarditis medical review form
eFigure. Flow diagram of cases of myocarditis and pericarditis reported to Vaccine Adverse Event Reporting System (VAERS) after receiving mRNA-based COVID-19 vaccine, United States, December 14, 2020-August 31, 2021.
eTable 1. Characteristics of all myocarditis cases reported to Vaccine Adverse Event Reporting System (VAERS) after mRNA-based COVID-19 vaccination, United States, December 14, 2020–August 31, 2021.
eTable 2. Characteristics of all pericarditis cases reported to Vaccine Adverse Event Reporting System (VAERS) after mRNA-based COVID-19 vaccination, United States, December 14, 2020–August 31, 2021.
eTable 3. Characteristics of myocarditis cases reported to Vaccine Adverse Event Reporting System after mRNA-based COVID-19 vaccination by case definition status.
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Oster ME , Shay DK , Su JR, et al. Myocarditis Cases Reported After mRNA-Based COVID-19 Vaccination in the US From December 2020 to August 2021. JAMA. 2022;327(4):331–340. doi:10.1001/jama.2021.24110
© 2024
Question What is the risk of myocarditis after mRNA-based COVID-19 vaccination in the US?
Findings In this descriptive study of 1626 cases of myocarditis in a national passive reporting system, the crude reporting rates within 7 days after vaccination exceeded the expected rates across multiple age and sex strata. The rates of myocarditis cases were highest after the second vaccination dose in adolescent males aged 12 to 15 years (70.7 per million doses of the BNT162b2 vaccine), in adolescent males aged 16 to 17 years (105.9 per million doses of the BNT162b2 vaccine), and in young men aged 18 to 24 years (52.4 and 56.3 per million doses of the BNT162b2 vaccine and the mRNA-1273 vaccine, respectively).
Meaning Based on passive surveillance reporting in the US, the risk of myocarditis after receiving mRNA-based COVID-19 vaccines was increased across multiple age and sex strata and was highest after the second vaccination dose in adolescent males and young men.
Importance Vaccination against COVID-19 provides clear public health benefits, but vaccination also carries potential risks. The risks and outcomes of myocarditis after COVID-19 vaccination are unclear.
Objective To describe reports of myocarditis and the reporting rates after mRNA-based COVID-19 vaccination in the US.
Design, Setting, and Participants Descriptive study of reports of myocarditis to the Vaccine Adverse Event Reporting System (VAERS) that occurred after mRNA-based COVID-19 vaccine administration between December 2020 and August 2021 in 192 405 448 individuals older than 12 years of age in the US; data were processed by VAERS as of September 30, 2021.
Exposures Vaccination with BNT162b2 (Pfizer-BioNTech) or mRNA-1273 (Moderna).
Main Outcomes and Measures Reports of myocarditis to VAERS were adjudicated and summarized for all age groups. Crude reporting rates were calculated across age and sex strata. Expected rates of myocarditis by age and sex were calculated using 2017-2019 claims data. For persons younger than 30 years of age, medical record reviews and clinician interviews were conducted to describe clinical presentation, diagnostic test results, treatment, and early outcomes.
Results Among 192 405 448 persons receiving a total of 354 100 845 mRNA-based COVID-19 vaccines during the study period, there were 1991 reports of myocarditis to VAERS and 1626 of these reports met the case definition of myocarditis. Of those with myocarditis, the median age was 21 years (IQR, 16-31 years) and the median time to symptom onset was 2 days (IQR, 1-3 days). Males comprised 82% of the myocarditis cases for whom sex was reported. The crude reporting rates for cases of myocarditis within 7 days after COVID-19 vaccination exceeded the expected rates of myocarditis across multiple age and sex strata. The rates of myocarditis were highest after the second vaccination dose in adolescent males aged 12 to 15 years (70.7 per million doses of the BNT162b2 vaccine), in adolescent males aged 16 to 17 years (105.9 per million doses of the BNT162b2 vaccine), and in young men aged 18 to 24 years (52.4 and 56.3 per million doses of the BNT162b2 vaccine and the mRNA-1273 vaccine, respectively). There were 826 cases of myocarditis among those younger than 30 years of age who had detailed clinical information available; of these cases, 792 of 809 (98%) had elevated troponin levels, 569 of 794 (72%) had abnormal electrocardiogram results, and 223 of 312 (72%) had abnormal cardiac magnetic resonance imaging results. Approximately 96% of persons (784/813) were hospitalized and 87% (577/661) of these had resolution of presenting symptoms by hospital discharge. The most common treatment was nonsteroidal anti-inflammatory drugs (589/676; 87%).
Conclusions and Relevance Based on passive surveillance reporting in the US, the risk of myocarditis after receiving mRNA-based COVID-19 vaccines was increased across multiple age and sex strata and was highest after the second vaccination dose in adolescent males and young men. This risk should be considered in the context of the benefits of COVID-19 vaccination.
Myocarditis is an inflammatory condition of the heart muscle that has a bimodal peak incidence during infancy and adolescence or young adulthood. 1 - 4 The clinical presentation and course of myocarditis is variable, with some patients not requiring treatment and others experiencing severe heart failure that requires subsequent heart transplantation or leads to death. 5 Onset of myocarditis typically follows an inciting process, often a viral illness; however, no antecedent cause is identified in many cases. 6 It has been hypothesized that vaccination can serve as a trigger for myocarditis; however, only the smallpox vaccine has previously been causally associated with myocarditis based on reports among US military personnel, with cases typically occurring 7 to 12 days after vaccination. 7
With the implementation of a large-scale, national COVID-19 vaccination program starting in December 2020, the US Centers for Disease Control and Prevention (CDC) and the US Food and Drug Administration began monitoring for a number of adverse events of special interest, including myocarditis and pericarditis, in the Vaccine Adverse Event Reporting System (VAERS), a long-standing national spontaneous reporting (passive surveillance) system. 8 As the reports of myocarditis after COVID-19 vaccination were reported to VAERS, the Clinical Immunization Safety Assessment Project, 9 a collaboration between the CDC and medical research centers, which includes physicians treating infectious diseases and other specialists (eg, cardiologists), consulted on several of the cases. In addition, reports from several countries raised concerns that mRNA-based COVID-19 vaccines may be associated with acute myocarditis. 10 - 15
Given this concern, the aims were to describe reports and confirmed cases of myocarditis initially reported to VAERS after mRNA-based COVID-19 vaccination and to provide estimates of the risk of myocarditis after mRNA-based COVID-19 vaccination based on age, sex, and vaccine type.
VAERS is a US spontaneous reporting (passive surveillance) system that functions as an early warning system for potential vaccine adverse events. 8 Co-administered by the CDC and the US Food and Drug Administration, VAERS accepts reports of all adverse events after vaccination from patients, parents, clinicians, vaccine manufacturers, and others regardless of whether the events could plausibly be associated with receipt of the vaccine. Reports to VAERS include information about the vaccinated person, the vaccine or vaccines administered, and the adverse events experienced by the vaccinated person. The reports to VAERS are then reviewed by third-party professional coders who have been trained in the assignment of Medical Dictionary for Regulatory Activities preferred terms. 16 The coders then assign appropriate terms based on the information available in the reports.
This activity was reviewed by the CDC and was conducted to be consistent with applicable federal law and CDC policy. The activities herein were confirmed to be nonresearch under the Common Rule in accordance with institutional procedures and therefore were not subject to institutional review board requirements. Informed consent was not obtained for this secondary use of existing information; see 45 CFR part 46.102(l)(2), 21 CFR part 56, 42 USC §241(d), 5 USC §552a, and 44 USC §3501 et seq.
The exposure of concern was vaccination with one of the mRNA-based COVID-19 vaccines: the BNT162b2 vaccine (Pfizer-BioNTech) or the mRNA-1273 vaccine (Moderna). During the analytic period, persons aged 12 years or older were eligible for the BNT162b2 vaccine and persons aged 18 years or older were eligible for the mRNA-1273 vaccine. The number of COVID-19 vaccine doses administered during the analytic period was obtained through the CDC’s COVID-19 Data Tracker. 17
The primary outcome was the occurrence of myocarditis and the secondary outcome was pericarditis. Reports to VAERS with these outcomes were initially characterized using the Medical Dictionary for Regulatory Activities preferred terms of myocarditis or pericarditis (specific terms are listed in the eMethods in the Supplement ). After initial review of reports of myocarditis to VAERS and review of the patient’s medical records (when available), the reports were further reviewed by CDC physicians and public health professionals to verify that they met the CDC’s case definition for probable or confirmed myocarditis (descriptions previously published and included in the eMethods in the Supplement ). 18 The CDC’s case definition of probable myocarditis requires the presence of new concerning symptoms, abnormal cardiac test results, and no other identifiable cause of the symptoms and findings. Confirmed cases of myocarditis further require histopathological confirmation of myocarditis or cardiac magnetic resonance imaging (MRI) findings consistent with myocarditis.
Deaths were included only if the individual had met the case definition for confirmed myocarditis and there was no other identifiable cause of death. Individual cases not involving death were included only if the person had met the case definition for probable myocarditis or confirmed myocarditis.
We characterized reports of myocarditis or pericarditis after COVID-19 vaccination that met the CDC’s case definition and were received by VAERS between December 14, 2020 (when COVID-19 vaccines were first publicly available in the US), and August 31, 2021, by age, sex, race, ethnicity, and vaccine type; data were processed by VAERS as of September 30, 2021. Race and ethnicity were optional fixed categories available by self-identification at the time of vaccination or by the individual filing a VAERS report. Race and ethnicity were included to provide the most complete baseline description possible for individual reports; however, further analyses were not stratified by race and ethnicity due to the high percentage of missing data. Reports of pericarditis with evidence of potential myocardial involvement were included in the review of reports of myocarditis. The eFigure in the Supplement outlines the categorization of the reports of myocarditis and pericarditis reviewed.
Further analyses were conducted only for myocarditis because of the preponderance of those reports to VAERS, in Clinical Immunization Safety Assessment Project consultations, and in published articles. 10 - 12 , 19 - 21 Crude reporting rates for myocarditis during a 7-day risk interval were calculated using the number of reports of myocarditis to VAERS per million doses of COVID-19 vaccine administered during the analytic period and stratified by age, sex, vaccination dose (first, second, or unknown), and vaccine type. Expected rates of myocarditis by age and sex were calculated using 2017-2019 data from the IBM MarketScan Commercial Research Database. This database contains individual-level, deidentified, inpatient and outpatient medical and prescription drug claims, and enrollment information submitted to IBM Watson Health by large employers and health plans. The data were accessed using version 4.0 of the IBM MarketScan Treatment Pathways analytic platform. Age- and sex-specific rates were calculated by determining the number of individuals with myocarditis ( International Statistical Classification of Diseases and Related Health Problems, Tenth Revision [ICD-10] codes B33.20, B33.22, B33.24, I40.0, I40.1, I40.8, I40.9, or I51.4) 22 identified during an inpatient encounter in 2017-2019 relative to the number of individuals of similar age and sex who were continually enrolled during the year in which the myocarditis-related hospitalization occurred; individuals with any diagnosis of myocarditis prior to that year were excluded. Given the limitations of the IBM MarketScan Commercial Research Database to capture enrollees aged 65 years or older, an expected rate for myocarditis was not calculated for this population. A 95% CI was calculated using Poisson distribution in SAS version 9.4 (SAS Institute Inc) for each expected rate of myocarditis and for each observed rate in a strata with at least 1 case.
In cases of probable or confirmed myocarditis among those younger than 30 years of age, their clinical course was then summarized to the extent possible based on medical review and clinician interviews. This clinical course included presenting symptoms, diagnostic test results, treatment, and early outcomes (abstraction form appears in the eMethods in the Supplement ). 23
When applicable, missing data were delineated in the results or the numbers with complete data were listed. No assumptions or imputations were made regarding missing data. Any percentages that were calculated included only those cases of myocarditis with adequate data to calculate the percentages.
Between December 14, 2020, and August 31, 2021, 192 405 448 individuals older than 12 years of age received a total of 354 100 845 mRNA-based COVID-19 vaccines. VAERS received 1991 reports of myocarditis (391 of which also included pericarditis) after receipt of at least 1 dose of mRNA-based COVID-19 vaccine (eTable 1 in the Supplement ) and 684 reports of pericarditis without the presence of myocarditis (eTable 2 in the Supplement ).
Of the 1991 reports of myocarditis, 1626 met the CDC’s case definition for probable or confirmed myocarditis ( Table 1 ). There were 208 reports that did not meet the CDC’s case definition for myocarditis and 157 reports that required more information to perform adjudication (eTable 3 in the Supplement ). Of the 1626 reports that met the CDC’s case definition for myocarditis, 1195 (73%) were younger than 30 years of age, 543 (33%) were younger than 18 years of age, and the median age was 21 years (IQR, 16-31 years) ( Figure 1 ). Of the reports of myocarditis with dose information, 82% (1265/1538) occurred after the second vaccination dose. Of those with a reported dose and time to symptom onset, the median time from vaccination to symptom onset was 3 days (IQR, 1-8 days) after the first vaccination dose and 74% (187/254) of myocarditis events occurred within 7 days. After the second vaccination dose, the median time to symptom onset was 2 days (IQR, 1-3 days) and 90% (1081/1199) of myocarditis events occurred within 7 days ( Figure 2 ).
Males comprised 82% (1334/1625) of the cases of myocarditis for whom sex was reported. The largest proportions of cases of myocarditis were among White persons (non-Hispanic or ethnicity not reported; 69% [914/1330]) and Hispanic persons (of all races; 17% [228/1330]). Among persons younger than 30 years of age, there were no confirmed cases of myocarditis in those who died after mRNA-based COVID-19 vaccination without another identifiable cause and there was 1 probable case of myocarditis but there was insufficient information available for a thorough investigation. At the time of data review, there were 2 reports of death in persons younger than 30 years of age with potential myocarditis that remain under investigation and are not included in the case counts.
Symptom onset of myocarditis was within 7 days after vaccination for 947 reports of individuals who received the BNT162b2 vaccine and for 382 reports of individuals who received the mRNA-1273 vaccine. The rates of myocarditis varied by vaccine type, sex, age, and first or second vaccination dose ( Table 2 ). The reporting rates of myocarditis were highest after the second vaccination dose in adolescent males aged 12 to 15 years (70.73 [95% CI, 61.68-81.11] per million doses of the BNT162b2 vaccine), in adolescent males aged 16 to 17 years (105.86 [95% CI, 91.65-122.27] per million doses of the BNT162b2 vaccine), and in young men aged 18 to 24 years (52.43 [95% CI, 45.56-60.33] per million doses of the BNT162b2 vaccine and 56.31 [95% CI, 47.08-67.34] per million doses of the mRNA-1273 vaccine). The lower estimate of the 95% CI for reporting rates of myocarditis in adolescent males and young men exceeded the upper bound of the expected rates after the first vaccination dose with the BNT162b2 vaccine in those aged 12 to 24 years, after the second vaccination dose with the BNT162b2 vaccine in those aged 12 to 49 years, after the first vaccination dose with the mRNA-1273 vaccine in those aged 18 to 39 years, and after the second vaccination dose with the mRNA-1273 vaccine in those aged 18 to 49 years.
The reporting rates of myocarditis in females were lower than those in males across all age strata younger than 50 years of age. The reporting rates of myocarditis were highest after the second vaccination dose in adolescent females aged 12 to 15 years (6.35 [95% CI, 4.05-9.96] per million doses of the BNT162b2 vaccine), in adolescent females aged 16 to 17 years (10.98 [95% CI, 7.16-16.84] per million doses of the BNT162b2 vaccine), in young women aged 18 to 24 years (6.87 [95% CI, 4.27-11.05] per million doses of the mRNA-1273 vaccine), and in women aged 25 to 29 years (8.22 [95% CI, 5.03-13.41] per million doses of the mRNA-1273 vaccine). The lower estimate of the 95% CI for reporting rates of myocarditis in females exceeded the upper bound of the expected rates after the second vaccination dose with the BNT162b2 vaccine in those aged 12 to 29 years and after the second vaccination dose with the mRNA-1273 vaccine in those aged 18 to 29 years.
Among the 1372 reports of myocarditis in persons younger than 30 years of age, 1305 were able to be adjudicated, with 92% (1195/1305) meeting the CDC’s case definition. Of these, chart abstractions or medical interviews were completed for 69% (826/1195) ( Table 3 ). The symptoms commonly reported in the verified cases of myocarditis in persons younger than 30 years of age included chest pain, pressure, or discomfort (727/817; 89%) and dyspnea or shortness of breath (242/817; 30%). Troponin levels were elevated in 98% (792/809) of the cases of myocarditis. The electrocardiogram result was abnormal in 72% (569/794) of cases of myocarditis. Of the patients who had received a cardiac MRI, 72% (223/312) had abnormal findings consistent with myocarditis. The echocardiogram results were available for 721 cases of myocarditis; of these, 84 (12%) demonstrated a notable decreased left ventricular ejection fraction (<50%). Among the 676 cases for whom treatment data were available, 589 (87%) received nonsteroidal anti-inflammatory drugs. Intravenous immunoglobulin and glucocorticoids were each used in 12% of the cases of myocarditis (78/676 and 81/676, respectively). Intensive therapies such as vasoactive medications (12 cases of myocarditis) and intubation or mechanical ventilation (2 cases) were rare. There were no verified cases of myocarditis requiring a heart transplant, extracorporeal membrane oxygenation, or a ventricular assist device. Of the 96% (784/813) of cases of myocarditis who were hospitalized, 98% (747/762) were discharged from the hospital at time of review. In 87% (577/661) of discharged cases of myocarditis, there was resolution of the presenting symptoms by hospital discharge.
In this review of reports to VAERS between December 2020 and August 2021, myocarditis was identified as a rare but serious adverse event that can occur after mRNA-based COVID-19 vaccination, particularly in adolescent males and young men. However, this increased risk must be weighed against the benefits of COVID-19 vaccination. 18
Compared with cases of non–vaccine-associated myocarditis, the reports of myocarditis to VAERS after mRNA-based COVID-19 vaccination were similar in demographic characteristics but different in their acute clinical course. First, the greater frequency noted among vaccine recipients aged 12 to 29 years vs those aged 30 years or older was similar to the age distribution seen in typical cases of myocarditis. 2 , 4 This pattern may explain why cases of myocarditis were not discovered until months after initial Emergency Use Authorization of the vaccines in the US (ie, until the vaccines were widely available to younger persons). Second, the sex distribution in cases of myocarditis after COVID-19 vaccination was similar to that seen in typical cases of myocarditis; there is a strong male predominance for both conditions. 2 , 4
However, the onset of myocarditis symptoms after exposure to a potential immunological trigger was shorter for COVID-19 vaccine–associated cases of myocarditis than is typical for myocarditis cases diagnosed after a viral illness. 24 - 26 Cases of myocarditis reported after COVID-19 vaccination were typically diagnosed within days of vaccination, whereas cases of typical viral myocarditis can often have indolent courses with symptoms sometimes present for weeks to months after a trigger if the cause is ever identified. 1 The major presenting symptoms appeared to resolve faster in cases of myocarditis after COVID-19 vaccination than in typical viral cases of myocarditis. Even though almost all individuals with cases of myocarditis were hospitalized and clinically monitored, they typically experienced symptomatic recovery after receiving only pain management. In contrast, typical viral cases of myocarditis can have a more variable clinical course. For example, up to 6% of typical viral myocarditis cases in adolescents require a heart transplant or result in mortality. 27
In the current study, the initial evaluation and treatment of COVID-19 vaccine–associated myocarditis cases was similar to that of typical myocarditis cases. 28 - 31 Initial evaluation usually included measurement of troponin level, electrocardiography, and echocardiography. 1 Cardiac MRI was often used for diagnostic purposes and also for possible prognostic purposes. 32 , 33 Supportive care was a mainstay of treatment, with specific cardiac or intensive care therapies as indicated by the patient’s clinical status.
Long-term outcome data are not yet available for COVID-19 vaccine–associated myocarditis cases. The CDC has started active follow-up surveillance in adolescents and young adults to assess the health and functional status and cardiac outcomes at 3 to 6 months in probable and confirmed cases of myocarditis reported to VAERS after COVID-19 vaccination. 34 For patients with myocarditis, the American Heart Association and the American College of Cardiology guidelines advise that patients should be instructed to refrain from competitive sports for 3 to 6 months, and that documentation of a normal electrocardiogram result, ambulatory rhythm monitoring, and an exercise test should be obtained prior to resumption of sports. 35 The use of cardiac MRI is unclear, but it may be useful in evaluating the progression or resolution of myocarditis in those with abnormalities on the baseline cardiac MRI. 36 Further doses of mRNA-based COVID-19 vaccines should be deferred, but may be considered in select circumstances. 37
This study has several limitations. First, although clinicians are required to report serious adverse events after COVID-19 vaccination, including all events leading to hospitalization, VAERS is a passive reporting system. As such, the reports of myocarditis to VAERS may be incomplete, and the quality of the information reported is variable. Missing data for sex, vaccination dose number, and race and ethnicity were not uncommon in the reports received; history of prior SARS-CoV-2 infection also was not known. Furthermore, as a passive system, VAERS data are subject to reporting biases in that both underreporting and overreporting are possible. 38 Given the high verification rate of reports of myocarditis to VAERS after mRNA-based COVID-19 vaccination, underreporting is more likely. Therefore, the actual rates of myocarditis per million doses of vaccine are likely higher than estimated.
Second, efforts by CDC investigators to obtain medical records or interview physicians were not always successful despite the special allowance for sharing information with the CDC under the Health Insurance Portability and Accountability Act of 1996. 39 This challenge limited the ability to perform case adjudication and complete investigations for some reports of myocarditis, although efforts are still ongoing when feasible.
Third, the data from vaccination administration were limited to what is reported to the CDC and thus may be incomplete, particularly with regard to demographics.
Fourth, calculation of expected rates from the IBM MarketScan Commercial Research Database relied on administrative data via the use of ICD-10 codes and there was no opportunity for clinical review. Furthermore, these data had limited information regarding the Medicare population; thus expected rates for those older than 65 years of age were not calculated. However, it is expected that the rates in those older than 65 years of age would not be higher than the rates in those aged 50 to 64 years. 4
Based on passive surveillance reporting in the US, the risk of myocarditis after receiving mRNA-based COVID-19 vaccines was increased across multiple age and sex strata and was highest after the second vaccination dose in adolescent males and young men. This risk should be considered in the context of the benefits of COVID-19 vaccination.
Corresponding Author: Matthew E. Oster, MD, MPH, US Centers for Disease Control and Prevention, 1600 Clifton Rd, Atlanta, GA 30333 ( [email protected] ).
Correction: This article was corrected March 21, 2022, to change “pericarditis” to “myocarditis” in the first row, first column of eTable 1 in the Supplement.
Accepted for Publication: December 16, 2021.
Author Contributions: Drs Oster and Su had full access to all of the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.
Concept and design: Oster, Shay, Su, Creech, Edwards, Dendy, Schlaudecker, Woo, Shimabukuro.
Acquisition, analysis, or interpretation of data: Oster, Shay, Su, Gee, Creech, Broder, Edwards, Soslow, Schlaudecker, Lang, Barnett, Ruberg, Smith, Campbell, Lopes, Sperling, Baumblatt, Thompson, Marquez, Strid, Woo, Pugsley, Reagan-Steiner, DeStefano, Shimabukuro.
Drafting of the manuscript: Oster, Shay, Su, Gee, Creech, Marquez, Strid, Woo, Shimabukuro.
Critical revision of the manuscript for important intellectual content: Oster, Shay, Su, Creech, Broder, Edwards, Soslow, Dendy, Schlaudecker, Lang, Barnett, Ruberg, Smith, Campbell, Lopes, Sperling, Baumblatt, Thompson, Pugsley, Reagan-Steiner, DeStefano, Shimabukuro.
Statistical analysis: Oster, Su, Marquez, Strid, Woo, Shimabukuro.
Obtained funding: Edwards, DeStefano.
Administrative, technical, or material support: Oster, Gee, Creech, Broder, Edwards, Soslow, Schlaudecker, Smith, Baumblatt, Thompson, Reagan-Steiner, DeStefano.
Supervision: Su, Edwards, Soslow, Dendy, Schlaudecker, Campbell, Sperling, DeStefano, Shimabukuro.
Conflict of Interest Disclosures: Dr Creech reported receiving grants from the National Institutes of Health for the Moderna and Janssen clinical trials and receiving personal fees from Astellas and Horizon. Dr Edwards reported receiving grants from the National Institutes of Health; receiving personal fees from BioNet, IBM, X-4 Pharma, Seqirus, Roche, Pfizer, Merck, Moderna, and Sanofi; and receiving compensation for being the associate editor of Clinical Infectious Diseases . Dr Soslow reported receiving personal fees from Esperare. Dr Schlaudecker reported receiving grants from Pfizer and receiving personal fees from Sanofi Pasteur. Drs Barnett, Ruberg, and Smith reported receiving grants from Pfizer. Dr Lopes reported receiving personal fees from Bayer, Boehringer Ingleheim, Bristol Myers Squibb, Daiichi Sankyo, GlaxoSmithKline, Medtronic, Merck, Pfizer, Portola, and Sanofi and receiving grants from Bristol Myers Squibb, GlaxoSmithKline, Medtronic, Pfizer, and Sanofi. No other disclosures were reported.
Funding/Support: This work was supported by contracts 200-2012-53709 (Boston Medical Center), 200-2012-53661 (Cincinnati Children’s Hospital Medical Center), 200-2012-53663 (Duke University), and 200-2012-50430 (Vanderbilt University Medical Center) with the US Centers for Disease Control and Prevention (CDC) Clinical Immunization Safety Assessment Project.
Role of the Funder/Sponsor: The CDC provided funding via the Clinical Immunization Safety Assessment Project to Drs Creech, Edwards, Soslow, Dendy, Schlaudecker, Lang, Barnett, Ruberg, Smith, Campbell, and Lopes. The authors affiliated with the CDC along with the other coauthors conducted the investigations; performed collection, management, analysis, and interpretation of the data; were involved in the preparation, review, and approval of the manuscript; and made the decision to submit the manuscript for publication.
Disclaimer: The findings and conclusions in this article are those of the authors and do not necessarily represent the official position of the CDC or the US Food and Drug Administration. Mention of a product or company name is for identification purposes only and does not constitute endorsement by the CDC or the US Food and Drug Administration.
Additional Contributions: We thank the following CDC staff who contributed to this article without compensation outside their normal salaries (in alphabetical order and contribution specified in parenthesis at end of each list of names): Nickolas Agathis, MD, MPH, Stephen R. Benoit, MD, MPH, Beau B. Bruce, MD, PhD, Abigail L. Carlson, MD, MPH, Meredith G. Dixon, MD, Jonathan Duffy, MD, MPH, Charles Duke, MD, MPH, Charles Edge, MSN, MS, Robyn Neblett Fanfair, MD, MPH, Nathan W. Furukawa, MD, MPH, Gavin Grant, MD, MPH, Grace Marx, MD, MPH, Maureen J. Miller, MD, MPH, Pedro Moro, MD, MPH, Meredith Oakley, DVM, MPH, Kia Padgett, MPH, BSN, RN, Janice Perez-Padilla, MPH, BSN, RN, Robert Perry, MD, MPH, Nimia Reyes, MD, MPH, Ernest E. Smith, MD, MPH&TM, David Sniadack, MD, MPH, Pamela Tucker, MD, Edward C. Weiss, MD, MPH, Erin Whitehouse, PhD, MPH, RN, Pascale M. Wortley, MD, MPH, and Rachael Zacks, MD (for clinical investigations and interviews); Amelia Jazwa, MSPH, Tara Johnson, MPH, MS, and Jamila Shields, MPH (for project coordination); Charles Licata, PhD, and Bicheng Zhang, MS (for data acquisition and organization); Charles E. Rose, PhD (for statistical consultation); and Scott D. Grosse, PhD (for calculation of expected rates of myocarditis). We also thank the clinical staff who cared for these patients and reported the adverse events to the Vaccine Adverse Event Reporting System.
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Article 18 Around the World (35 Minutes) Students will analyze a real-world case study related to freedom of religion. Distribute both the Universal Declaration of Human Rights and the Around the World Case Studies to each student.
The importance of freedom of religious or belief (FoRB) protections, as expressed in Article 18 of the Universal Declaration of Human Rights (UDHR) is not widely understood outside academic and legal circles. There are a sizeable number of organisations endeavouring to change this, but for Article 18 to be fully understood, it must be reinterpreted and reaffirmed in every generation across all ...
The idea that the abusive or bad faith exercise of a right/power must be sanctioned is a long-standing idea in domestic law 4 and has also seen debates in international law. 5 The more specific prohibition on the use of a power for purposes other than what is legally proscribed ("détournement de pouvoir") is found in the administrative law of many domestic systems 6 and is treated by some ...
A condition referred to as slimmer's paralysis or peroneal nerve neuropathy can occur in patients following a rapid and significant weight reduction. This case study focuses on the presentation of a 49-year-old female who suffered from unilateral foot drop after an extreme weight loss over 6 months while taking a GLP-1 receptor agonist for obesity management. On the basis of history ...
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A case study is one of the most commonly used methodologies of social research. This article attempts to look into the various dimensions of a case study research strategy, the different epistemological strands which determine the particular case study type and approach adopted in the field, discusses the factors which can enhance the effectiveness of a case study research, and the debate ...
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Article 18 (1): The first clause is for the state's responsibility. Article 18 (1) prohibits all titles. It prevents the government from bestowing titles on anyone, whether a citizen or a non-citizen, apart from the titles in the fields of military and academic, for example, Paramveer, Doctor, etc. As a result, a university might bestow a ...
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Case studies are good for describing, comparing, evaluating and understanding different aspects of a research problem. Table of contents. When to do a case study. Step 1: Select a case. Step 2: Build a theoretical framework. Step 3: Collect your data. Step 4: Describe and analyze the case.
Article 18- Abolition of Titles. (1) No title, not being a military or academic distinction, shall be conferred by the State. (2) No citizen of India shall accept any title from any foreign State. (3) No person who is not a citizen of India shall, while he holds any office of profit or trust under the State, accept without the consent of the ...
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Case study is a research methodology, typically seen in social and life sciences. There is no one definition of case study research.1 However, very simply… 'a case study can be defined as an intensive study about a person, a group of people or a unit, which is aimed to generalize over several units'.1 A case study has also been described as an intensive, systematic investigation of a ...
A case study is a research method that involves an in-depth analysis of a real-life phenomenon or situation. Learn how to write a case study for your social sciences research assignments with this helpful guide from USC Library. Find out how to define the case, select the data sources, analyze the evidence, and report the results.
In this article, we explore the concept of a case study, including its writing process, benefits, various types, challenges, and more.. How to write a case study. Understanding how to write a case study is an invaluable skill. You'll need to embrace decision-making - from deciding which customers to feature to designing the best format to make them as engaging as possible.
Article 18 (1) abolishes all titles. It prohibits the State to confer titles on anybody whether a citizen or a non-citizen. Military and academic distinctions are, however, exempted from the prohibition. Thus, a university can give title or honor on a man of merit. Clause (2) prohibits a citizen of India from accepting any title from any ...
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Abstract Background Healthcare-associated infections (HAIs) are one of the most common adverse events in healthcare and represent a major public health problem. However, 40% to 70% of HAIs are considered to be preventable. The present study was conducted to analyze the incidence, etiological factors, and outcomes of HAIs through active surveillance in three hospitals in the city of Bobo Dioulasso.
The pressure to do more, to be more, is fueling its own silent epidemic. Lauren Cohen discusses the common misperceptions that get in the way of supporting employees' well-being, drawing on case studies about people who have been deeply affected by mental illness. 01 Jun 2023. HBS Case.
The definitions of case study evolved over a period of time. Case study is defined as "a systematic inquiry into an event or a set of related events which aims to describe and explain the phenomenon of interest" (Bromley, 1990).Stoecker defined a case study as an "intensive research in which interpretations are given based on observable concrete interconnections between actual properties ...
The Case Analysis Coach is an interactive tutorial on reading and analyzing a case study. The Case Study Handbook covers key skills students need to read, understand, discuss and write about cases. The Case Study Handbook is also available as individual chapters to help your students focus on specific skills.
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Give students an opportunity to practice the case analysis methodology via an ungraded sample case study. Designate groups of five to seven students to discuss the case and the six steps in breakout sessions (in class or via Zoom). Ensure case analyses are weighted heavily as a grading component. We suggest 30-50 percent of the overall course ...
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