Impacts of compounding drought and heatwave events on child mental health: insights from a spatial clustering analysis.

BACKGROUND: Concurrent heatwave and drought events may have larger health impacts than each event separately; however, no US-based studies have examined differential mental health impacts of compound drought and heatwave events in pediatric populations. OBJECTIVE: To examine the spatial patterns of mood disorders and suicide-related emergency department (ED) visits in children during heatwave, drought, and compound heatwave and drought events. We tested whether the occurrence of compound heatwave and drought events have a synergistic (multiplicative) effect on the risk of mental health related outcomes in children as compared to the additive effect of each individual climate hazard. Lastly, we identified household and community-level determinants of geographic variability of high psychiatric burden. METHODS: Daily counts of psychiatric ED visits in North Carolina from 2016 to 2019 (May to Sept) for pediatric populations were aggregated at the county scale. Bernoulli cluster analyses identified high-risk spatial clusters of psychiatric morbidity during heatwave, drought, or compound heatwave and drought periods. Multivariate adaptive regression models examined the individual importance of household and community-level determinants in predicting high-risk clustering of mood disorders or suicidality across the three climate threats. RESULTS: Results showed significant spatial clustering of suicide and mood disorder risks in children during heatwave, drought, and compound event periods. Periods of drought were associated with the highest likelihood of spatial clustering for suicide and mood disorders, where the risk of an ED visit was 4.48 and 6.32 times higher, respectively, compared to non-drought periods. Compounding events were associated with a threefold increase in both suicide and mood disorder-related ED visits. Community and household vulnerability factors that most contributed to spatial clustering varied across climate hazards, but consistent determinants included residential segregation, green space availability, low English proficiency, overcrowding, no broadband access, no vehicle access, housing vacancy, and availability of housing units. CONCLUSION: Findings advance understanding on the locations of vulnerable pediatric populations who are disproportionately exposed to compounding climate stressors and identify community resilience factors to target in public health adaptation strategies.

A Difference-In Difference Analysis of the South Carolina 2015 Extreme Floods and the Association with Maternal Health.

Research documenting the public health impacts of natural disasters often focuses on adults and children. Little research has examined the influence of extreme events, like floods, on maternal health, and less has examined the effect of disasters on maternal indicators like severe maternal morbidity (SMM) or unexpected outcomes of labor and delivery that result in significant short-or long-term consequences to a woman's health. The aim of this study is to identify the impacts of the 2015 flood events on maternal health outcomes in South Carolina, USA. We employ a quasi-experimental design using a difference-in-difference analysis with log-binomial regressions to evaluate maternal outcomes for impacted and control locations during the disaster event. Unlike previous studies, we extended our difference-in-difference analysis to include a trimester of exposure to assess the timing of flood exposure. We did not find evidence of statistically significant main effects on maternal health from the 2015 flood events related to preterm birth, gestational diabetes, mental disorders of pregnancy, depression, and generalized anxiety. However, we did find a statistically significant increase in SMM and low birth weight during the flood event for women in select trimester periods who were directly exposed. Our work provides new evidence on the effects of extreme flood events, like the 2015 floods, which can impact maternal health during specific exposure periods of pregnancy. Additional research is needed across other extreme weather events, as the unique context of the 2015 floods limits the generalizability of our findings.

Southeastern United States Predictors of COVID-19 in Nursing Homes.

This study's aim was to determine nursing home (NH) and county-level predictors of COVID-19 outbreaks in nursing homes (NHs) in the southeastern region of the United States across three time periods. NH-level data compiled from census data and from NH compare and NH COVID-19 infection datasets provided by the Center for Medicare and Medicaid Services cover 2951 NHs located in 836 counties in nine states. A generalized linear mixed-effect model with a random effect was applied to significant factors identified in the final stepwise regression. County-level COVID-19 estimates and NHs with more certified beds were predictors of COVID-19 outbreaks in NHs across all time periods. Predictors of NH cases varied across the time periods with fewer community and NH variables predicting COVID-19 in NH during the late period. Future research should investigate predictors of COVID-19 in NH in other regions of the US from the early periods through March 2021.

Participatory COVID-19 Surveillance Tool in Rural Appalachia : Real-Time Disease Monitoring and Regional Response.

INTRODUCTION: Few US studies have examined the usefulness of participatory surveillance during the coronavirus disease 2019 (COVID-19) pandemic for enhancing local health response efforts, particularly in rural settings. We report on the development and implementation of an internet-based COVID-19 participatory surveillance tool in rural Appalachia. METHODS: A regional collaboration among public health partners culminated in the design and implementation of the COVID-19 Self-Checker, a local online symptom tracker. The tool collected data on participant demographic characteristics and health history. County residents were then invited to take part in an automated daily electronic follow-up to monitor symptom progression, assess barriers to care and testing, and collect data on COVID-19 test results and symptom resolution. RESULTS: Nearly 6500 county residents visited and 1755 residents completed the COVID-19 Self-Checker from April 30 through June 9, 2020. Of the 579 residents who reported severe or mild COVID-19 symptoms, COVID-19 symptoms were primarily reported among women (n = 408, 70.5%), adults with preexisting health conditions (n = 246, 70.5%), adults aged 18-44 (n = 301, 52.0%), and users who reported not having a health care provider (n = 131, 22.6%). Initial findings showed underrepresentation of some racial/ethnic and non-English-speaking groups. PRACTICAL IMPLICATIONS: This low-cost internet-based platform provided a flexible means to collect participatory surveillance data on local changes in COVID-19 symptoms and adapt to guidance. Data from this tool can be used to monitor the efficacy of public health response measures at the local level in rural Appalachia.

Examining the Feasibility of Smart Blood Pressure Home Monitoring: Advancing Remote Prenatal Care in Rural Appalachia.

Background: Hypertensive disorders of pregnancy are a leading cause of U.S. maternal morbidity and mortality. Home blood pressure (BP) monitoring can provide early detection of hypertension (HTN) outside of routine prenatal visits. Yet little is understood about how well self-monitored BP performs during pregnancy, particularly in rural America. Objective: To examine the feasibility and patient adherence to a self-monitoring BP program and to remotely collect data on pregnant women during the third trimester at a rural health clinic. Materials and Methods: A repeated-measures prospective design was used to remotely monitor home BP readings. We examined retention and persistence of weekly BP monitoring in late-stage pregnancy, differences between weekly self-monitored and clinic BP measures, the performance of self-monitored BP in early detection of pregnancy-induced HTN, and receptivity to technology-enabled prenatal monitoring. Results: A total of 30 women enrolled. Women reported high satisfaction with prenatal care, but missed 5 out of 13 clinic visits (54%). Women contributed an average of 31.2 days of home BP monitoring. Findings showed that home systolic and diastolic BP readings slightly varied from clinic readings. Women reported high health-related internet use and e-health literacy. Participants (93%, n = 25) reported a willingness to change their behavior during pregnancy in response to personalized recommendations from a smartphone. Although preliminary, we confirmed that remote monitoring can detect elevated BP earlier than in routine clinic visits. Conclusion: Findings from this study can be used to inform a novel remote monitoring protocol to improve pregnancy care in a rural care setting.

Use of wearable sensors for pregnancy health and environmental monitoring: Descriptive findings from the perspective of patients and providers.

BACKGROUND: Wearable sensors and other smart technology may be especially beneficial in providing remote monitoring of sub-clinical changes in pregnancy health status. Yet, limited research has examined perceptions among pregnant patients and providers in incorporating smart technology into their daily routine and clinical practice. OBJECTIVE: The purpose of this study was to examine the perceptions of pregnant women and their providers at a rural health clinic on the use of wearable technology to monitor health and environmental exposures during pregnancy. METHODS: An anonymous 21-item e-survey was administered to family medicine or obstetrics and gynecology (n=28) providers at a rural health clinic; while a 21-item paper survey was administered to pregnant women (n=103) attending the clinic for prenatal care. RESULTS: Smartphone and digital technology use was high among patients and providers. Patients would consider wearing a mobile sensor during pregnancy, reported no privacy concerns, and felt comfortable sharing information from these devices with their physician. About seven out of 10 women expressed willingness to change their behavior during pregnancy in response to receiving personalized recommendations from a smartphone. While most providers did not currently use smart technologies in their medical practice, about half felt it will be used more often in the future to diagnose and remotely monitor patients. Patients ranked fetal heart rate and blood pressure as their top preference for health monitoring compared to physicians who ranked blood pressure and blood glucose. Patients and providers demonstrated similar preferences for environmental monitoring, but patients as a whole expressed more interests in tracking environmental measures compared to their providers. CONCLUSIONS: Patients and providers responded positively to the use of wearable sensor technology in prenatal care. More research is needed to understand what factors might motivate provider use and implementation of wearable technology to improve the delivery of prenatal care.

Report-back for geo-referenced environmental data: A case study on personal monitoring of temperature in outdoor workers.

Few studies have evaluated the benefits of reporting back participatory environmental monitoring results, particularly regarding participant motivation toward behavioural modification concerning workplace heat exposure. This study evaluated the individual data report-back for geo-located environmental temperature and time activity patterns in grounds maintenance crews in three geographic regions across the South-eastern United States. Surveys collected information on worker interpretation of their results and intended action(s) to reduce heat exposure. Worker response was highly positive, especially among more experienced workers who expressed a greater willingness to modify personal behaviour to reduce heat stress. Individual-level report-back of environmental data is a powerful tool for individuals to understand and act on their personal exposure to heat.