Social media research during natural disasters has been presented as a tool to guide response and relief efforts in the disciplines of geography and computer sciences. This systematic review highlights the public health implications of social media use in the response phase of the emergency, assessing (1) how social media can improve the dissemination of emergency warning and response information during and after a natural disaster, and (2) how social media can help identify physical, medical, functional, and emotional needs after a natural disaster. We surveyed the literature using 3 databases and included 44 research articles. We found that analyses of social media data were performed using a wide range of spatiotemporal scales. Social media platforms were identified as broadcasting tools presenting an opportunity for public health agencies to share emergency warnings. Social media was used as a tool to identify areas in need of relief operations or medical assistance by using self-reported location, with map development as a common method to visualize data. In retrospective analyses, social media analysis showed promise as an opportunity to reduce the time of response and to identify the individuals’ location. Further research for misinformation and rumor control using social media is needed.

The Nepali population is among those most vulnerable to the health impacts of climate change. We conducted a systematic literature review to document the health effects of climate change in Nepal and identify knowledge gaps by examining vulnerability categories related to health. Three databases were searched for journal articles that addressed health and vulnerability related to climate change in Nepal from 2010 onwards. Of the 1063 articles identified, 37 were eligible for inclusion. The findings suggested the health of the population was affected mostly by food insecurity, floods, droughts, and reduced water levels. Studies revealed both morbidity and mortality increased due to climate change, with the most impacted populations being women, children, and the elderly. At greatest risk for impacts from climate change were those from poor and marginal populations, especially impoverished women. The public health sector, healthcare, and potable water sources were some of the least mentioned vulnerability subcategories, indicating more research is needed to better understand their adaptation capacities. We propose that identifying vulnerabilities and areas of limited research are critical steps in the prioritization of health policy and interventions for the most vulnerable populations in Nepal.

Mental health issues can reach epidemic proportions in developed countries after natural disasters, but research is needed to better understand the impact on children and adolescents in developing nations. A cross-sectional study was performed to examine the relationship between earthquake exposures and depression, PTSD, and resilience among children and adolescents in Phulpingdanda village in Nepal, 1 year after the 2015 earthquakes, using the Depression Self-Rating Scale for Children, Child PTSD Symptom Scale, and the Child and Youth Resilience Measure, respectively. To quantify exposure, a basic demographic and household questionnaire, including an earthquake exposure assessment tool for children and adolescents, was created. Of the 62 respondents interviewed, 3.23% and 4.84% displayed symptomatology of depression and PTSD. A large number of respondents interviewed scored high for resiliency (80.65%). All 62 respondents were displaced from their household and witnessed severe damage of both their homes and village. The number of earthquake exposures had a strong, positive correlation with PTSD symptomatology. Although the number of respondents who showed signs of depression and PTSD symptomatology was lower than anticipated, resilience scores were considerably higher. Future research should explore which protective factors may contribute to high resiliency in Nepali children and adolescents.

: This study characterized COVID-19 transmission in Ghana in 2020 and 2021 by estimating the time-varying reproduction number (R_t) and exploring its association with various public health interventions at the national and regional levels. Ghana experienced four pandemic waves, with epidemic peaks in July 2020 and January, August, and December 2021. The epidemic peak was the highest nationwide in December 2021 with R_t ≥ 2. Throughout 2020 and 2021, per-capita cumulative case count by region increased with population size. Mobility data suggested a negative correlation between R_t and staying home during the first 90 days of the pandemic. The relaxation of movement restrictions and religious gatherings was not associated with increased R_t in the regions with fewer case burdens. R_t decreased from > 1 when schools reopened in January 2021 to < 1 after vaccination rollout in March 2021. Findings indicated most public health interventions were associated with R_t reduction at the national and regional levels.

Systemic inequity concerning the social determinants of health has been known to affect morbidity and mortality for decades. Significant attention has focused on the individual-level demographic and co-morbid factors associated with rates and mortality of COVID-19. However, less attention has been given to the county-level social determinants of health that are the main drivers of health inequities. To identify the degree to which social determinants of health predict COVID-19 cumulative case rates at the county-level in Georgia, we performed a sequential, cross-sectional ecologic analysis using a diverse set of socioeconomic and demographic variables. Lasso regression was used to identify variables from collinear groups. Twelve variables correlated to cumulative case rates (for cases reported by 1 August 2020) with an adjusted r squared of 0.4525. As time progressed in the pandemic, correlation of demographic and socioeconomic factors to cumulative case rates increased, as did number of variables selected. Findings indicate the social determinants of health and demographic factors continue to predict case rates of COVID-19 at the county-level as the pandemic evolves. This research contributes to the growing body of evidence that health disparities continue to widen, disproportionality affecting vulnerable populations.