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1. Community Mobility and Depressive Symptoms During the COVID-19 Pandemic in the United States

   https://doi.org/10.1001/jamanetworkopen.2023.34945  

   Perlis, Roy H. ; Lunz Trujillo, Kristin ; Safarpour, Alauna ; Quintana, Alexi ; Simonson, Matthew D. ; Perlis, Jasper ; Santillana, Mauricio ; Ognyanova, Katherine ; Baum, Matthew A. ; Druckman, James N. ; et al ( September 2023 , JAMA Network Open)

   Marked elevation in levels of depressive symptoms compared with historical norms have been described during the COVID-19 pandemic, and understanding the extent to which these are associated with diminished in-person social interaction could inform public health planning for future pandemics or other disasters.

   To describe the association between living in a US county with diminished mobility during the COVID-19 pandemic and self-reported depressive symptoms, while accounting for potential local and state-level confounding factors.

   This survey study used 18 waves of a nonprobability internet survey conducted in the United States between May 2020 and April 2022. Participants included respondents who were 18 years and older and lived in 1 of the 50 US states or Washington DC.

   Depressive symptoms measured by the Patient Health Questionnaire-9 (PHQ-9); county-level community mobility estimates from mobile apps; COVID-19 policies at the US state level from the Oxford stringency index.

   The 192 271 survey respondents had a mean (SD) of age 43.1 (16.5) years, and 768 (0.4%) were American Indian or Alaska Native individuals, 11 448 (6.0%) were Asian individuals, 20 277 (10.5%) were Black individuals, 15 036 (7.8%) were Hispanic individuals, 1975 (1.0%) were Pacific Islander individuals, 138 702 (72.1%) were White individuals, and 4065 (2.1%) were individuals of another race. Additionally, 126 381 respondents (65.7%) identified as female and 65 890 (34.3%) as male. Mean (SD) depression severity by PHQ-9 was 7.2 (6.8). In a mixed-effects linear regression model, the mean county-level proportion of individuals not leaving home was associated with a greater level of depression symptoms (β, 2.58; 95% CI, 1.57-3.58) after adjustment for individual sociodemographic features. Results were similar after the inclusion in regression models of local COVID-19 activity, weather, and county-level economic features, and persisted after widespread availability of COVID-19 vaccination. They were attenuated by the inclusion of state-level pandemic restrictions. Two restrictions, mandatory mask-wearing in public (β, 0.23; 95% CI, 0.15-0.30) and policies cancelling public events (β, 0.37; 95% CI, 0.22-0.51), demonstrated modest independent associations with depressive symptom severity.

   In this study, depressive symptoms were greater in locales and times with diminished community mobility. Strategies to understand the potential public health consequences of pandemic responses are needed.

    

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2. Service delivery at Title X sites in Texas during the COVID ‐19 pandemic

   https://doi.org/10.1363/psrh.12211  

   Burke, Kristen Lagasse ; Sierra, Gracia ; Lerma, Klaira ; White, Kari ( November 2022 , Perspectives on Sexual and Reproductive Health)

   The important role of Title X sites in supporting publicly funded reproductive healthcare was elevated during the COVID‐19 pandemic, as many people experienced economic uncertainty and changed their fertility preferences. In this study, we assessed changes in service delivery during the first year of the COVID‐19 pandemic at Title X‐supported sites in Texas, a large state with a high uninsured rate and a diverse Title X network.

   Using surveys of Title X‐funded organizations in Texas from April and November 2020, we examined the percentage of organizations reporting service modifications. With administrative data on 507,947 client encounters between March 2019 and March 2021, we assessed change in client volume at the onset of the pandemic and evaluated the association between regional COVID‐19 case rates and the provision of key Title X services.

   In April 2020, most organizations (78%) limited in‐person operations while implementing telehealth (74%) and contactless contraception (67%). Network‐wide encounter volume declined by 26% at pandemic onset (incidence rate ratio [IRR] = 0.74, 95% confidence interval [CI] = 0.65, 0.84). Health departments experienced the steepest declines in encounter volume (IRR = 0.43, 95% CI = 0.36–0.50). Weekly encounters, particularly for long‐acting reversible method placement/removal and sexually transmitted infection testing, decreased as COVID‐19 rates increased.

   Investment in public health infrastructure, including providing robust support to health departments as well as rebuilding and expanding the Title X network, is essential to safeguarding access to publicly funded reproductive healthcare during and after the pandemic.

    

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3. Disparities in Water Quality in Indian Country

   Conroy-Ben, O. ; Richard, R. ( April 2018 , Journal of contemporary water research and education)

   Abstract: Tribal Nations in the United States are afflicted by a number of disparities including health, socioeconomics, education, and contaminant exposure to name a few. To understand drinking water quality disparities, we analyzed Safe Drinking Water Act violations in Indian Country found in the Environmental Protection Agency’s (EPA’s) Enforcement and Compliance History Online (ECHO) and compared them to violations in non-tribal areas of the same state for the time period 2014 – 2017. The violations assessed were total point accumulations per year per 1,000 customers, health-based maximum contaminant limit (MCL), reporting and monitoring, and public notice for each state reporting tribal data. Violation point disparities were evident, as tribal facilities acquired nearly six times the points of the national average. In some states, health-based tribal water quality was better than in non-tribal communities, however Arizona, Iowa, Idaho, Montana, Utah, and Wyoming had MCL violations affecting a greater percentage of tribal populations than non-tribal. Nation-wide, monitoring and reporting violations affected tribal communities at nearly twice the rate of non-tribal customers. Public notice reporting was high and comparable for both tribal and non-tribal facilities. Finally, a comparison of small drinking water facilities, under which ~97% of the surveyed tribal drinking water falls, confirmed state-wide disparities. Solutions for the apparent disparities in Indian Country and on non-tribal lands may be as simple as rectifying monitoring and reporting violations, though this correction will not shift the overall water quality difference. Addressing MCL and treatment violations is the next step to reduce the disparity. 

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4. Telehealth Challenges for California Rural Hospitals in Reaching Latino Populations During COVID-19

   https://doi.org/10.2196/41562  

   Mauricio, Noemi ; Newhart, Glen ; Herber, Steven ; Ahumada-Newhart, Veronica ( January 2023 , Journal of Medical Internet Research (JMIR), Iproceedings)

   Rural and remote communities were especially vulnerable to the COVID-19 pandemic due to the availability and capacity of rural health services. Research has found that key issues surrounded (1) the lack of staff, (2) the need for coordinated health services, and (3) operational and facility issues. Similarly, research also confirms that irrespective of hospital capacity issues existing during crisis, compared to urban communities, rural communities typically face poorer access to health services. Telehealth programs have long held promise for addressing health disparities perpetuated by inadequate health care access. In response to the current COVID-19 pandemic, Adventist Health Saint Helena Hospital, a rural hospital in northern California, urgently worked to expand telehealth services. However, as Adventist Health Saint Helena Hospital is the longest-serving rural hospital in the state of California, administrators were also able to draw on experiences from the pandemic of 1918/1919. Understanding their historically rural and heavily Latino populations, their telehealth approach was coupled with cultural approaches for prioritizing socially responsive and equitable access to health services.

   This study aimed to present one rural community’s holistic sociotechnical response to COVID-19 in redesigning their health care delivery approach. Redesign efforts included the expansion of digital health services coupled with county-wide collaborations for nondigital mobile health centers, testing, and vaccination clinics to meet the needs of those with limited digital access and language barriers.

   We present data on telehealth services for maintaining critical care services and a framework on the feasibility of private-public partnerships to address COVID-19 challenges.

   In this paper, we provide a critical review of how a rural hospital adapted its health care approach to incorporate telehealth services and distance services to meet the needs of a diverse population.

   This paper contributes empirical data on how rural communities can use telehealth technologies and community partnerships for a holistic community approach to meet health needs during a natural disaster.

   None declared.

    

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5. Predictive performance of multi-model ensemble forecasts of COVID-19 across European nations

   https://doi.org/10.7554/eLife.81916  

   Sherratt, Katharine ; Gruson, Hugo ; Grah, Rok ; Johnson, Helen ; Niehus, Rene ; Prasse, Bastian ; Sandmann, Frank ; Deuschel, Jannik ; Wolffram, Daniel ; Abbott, Sam ; et al ( April 2023 , eLife)

   Short-term forecasts of infectious disease burden can contribute to situational awareness and aid capacity planning. Based on best practice in other fields and recent insights in infectious disease epidemiology, one can maximise the predictive performance of such forecasts if multiple models are combined into an ensemble. Here, we report on the performance of ensembles in predicting COVID-19 cases and deaths across Europe between 08 March 2021 and 07 March 2022.

   We used open-source tools to develop a public European COVID-19 Forecast Hub. We invited groups globally to contribute weekly forecasts for COVID-19 cases and deaths reported by a standardised source for 32 countries over the next 1–4 weeks. Teams submitted forecasts from March 2021 using standardised quantiles of the predictive distribution. Each week we created an ensemble forecast, where each predictive quantile was calculated as the equally-weighted average (initially the mean and then from 26th July the median) of all individual models’ predictive quantiles. We measured the performance of each model using the relative Weighted Interval Score (WIS), comparing models’ forecast accuracy relative to all other models. We retrospectively explored alternative methods for ensemble forecasts, including weighted averages based on models’ past predictive performance.

   Over 52 weeks, we collected forecasts from 48 unique models. We evaluated 29 models’ forecast scores in comparison to the ensemble model. We found a weekly ensemble had a consistently strong performance across countries over time. Across all horizons and locations, the ensemble performed better on relative WIS than 83% of participating models’ forecasts of incident cases (with a total N=886 predictions from 23 unique models), and 91% of participating models’ forecasts of deaths (N=763 predictions from 20 models). Across a 1–4 week time horizon, ensemble performance declined with longer forecast periods when forecasting cases, but remained stable over 4 weeks for incident death forecasts. In every forecast across 32 countries, the ensemble outperformed most contributing models when forecasting either cases or deaths, frequently outperforming all of its individual component models. Among several choices of ensemble methods we found that the most influential and best choice was to use a median average of models instead of using the mean, regardless of methods of weighting component forecast models.

   Our results support the use of combining forecasts from individual models into an ensemble in order to improve predictive performance across epidemiological targets and populations during infectious disease epidemics. Our findings further suggest that median ensemble methods yield better predictive performance more than ones based on means. Our findings also highlight that forecast consumers should place more weight on incident death forecasts than incident case forecasts at forecast horizons greater than 2 weeks.

   AA, BH, BL, LWa, MMa, PP, SV funded by National Institutes of Health (NIH) Grant 1R01GM109718, NSF BIG DATA Grant IIS-1633028, NSF Grant No.: OAC-1916805, NSF Expeditions in Computing Grant CCF-1918656, CCF-1917819, NSF RAPID CNS-2028004, NSF RAPID OAC-2027541, US Centers for Disease Control and Prevention 75D30119C05935, a grant from Google, University of Virginia Strategic Investment Fund award number SIF160, Defense Threat Reduction Agency (DTRA) under Contract No. HDTRA1-19-D-0007, and respectively Virginia Dept of Health Grant VDH-21-501-0141, VDH-21-501-0143, VDH-21-501-0147, VDH-21-501-0145, VDH-21-501-0146, VDH-21-501-0142, VDH-21-501-0148. AF, AMa, GL funded by SMIGE - Modelli statistici inferenziali per governare l'epidemia, FISR 2020-Covid-19 I Fase, FISR2020IP-00156, Codice Progetto: PRJ-0695. AM, BK, FD, FR, JK, JN, JZ, KN, MG, MR, MS, RB funded by Ministry of Science and Higher Education of Poland with grant 28/WFSN/2021 to the University of Warsaw. BRe, CPe, JLAz funded by Ministerio de Sanidad/ISCIII. BT, PG funded by PERISCOPE European H2020 project, contract number 101016233. CP, DL, EA, MC, SA funded by European Commission - Directorate-General for Communications Networks, Content and Technology through the contract LC-01485746, and Ministerio de Ciencia, Innovacion y Universidades and FEDER, with the project PGC2018-095456-B-I00. DE., MGu funded by Spanish Ministry of Health / REACT-UE (FEDER). DO, GF, IMi, LC funded by Laboratory Directed Research and Development program of Los Alamos National Laboratory (LANL) under project number 20200700ER. DS, ELR, GG, NGR, NW, YW funded by National Institutes of General Medical Sciences (R35GM119582; the content is solely the responsibility of the authors and does not necessarily represent the official views of NIGMS or the National Institutes of Health). FB, FP funded by InPresa, Lombardy Region, Italy. HG, KS funded by European Centre for Disease Prevention and Control. IV funded by Agencia de Qualitat i Avaluacio Sanitaries de Catalunya (AQuAS) through contract 2021-021OE. JDe, SMo, VP funded by Netzwerk Universitatsmedizin (NUM) project egePan (01KX2021). JPB, SH, TH funded by Federal Ministry of Education and Research (BMBF; grant 05M18SIA). KH, MSc, YKh funded by Project SaxoCOV, funded by the German Free State of Saxony. Presentation of data, model results and simulations also funded by the NFDI4Health Task Force COVID-19 (https://www.nfdi4health.de/task-force-covid-19-2) within the framework of a DFG-project (LO-342/17-1). LP, VE funded by Mathematical and Statistical modelling project (MUNI/A/1615/2020), Online platform for real-time monitoring, analysis and management of epidemic situations (MUNI/11/02202001/2020); VE also supported by RECETOX research infrastructure (Ministry of Education, Youth and Sports of the Czech Republic: LM2018121), the CETOCOEN EXCELLENCE (CZ.02.1.01/0.0/0.0/17-043/0009632), RECETOX RI project (CZ.02.1.01/0.0/0.0/16-013/0001761). NIB funded by Health Protection Research Unit (grant code NIHR200908). SAb, SF funded by Wellcome Trust (210758/Z/18/Z).

    

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