Morgan Elizabeth Gorris

Many infectious disease forecasting models in the United States (US) are built with data partitioned into geopolitical regions centered on human activity as opposed to regions defined by natural ecosystems; although useful for data collection and intervention, this has the potential to mask biological relationships between the environment and disease. We explored this concept by analyzing the correlations between climate and West Nile virus (WNV) case data aggregated to geopolitical and ecological regions. We compared correlations between minimum, maximum, and mean annual temperature; precipitation; and annual WNV neuroinvasive disease (WNND) case data from 2005 to 2019 when partitioned into (a) climate regions defined by the National Oceanic and Atmospheric Administration (NOAA) and (b) Level I ecoregions defined by the Environmental Protection Agency (EPA). We found that correlations between climate and WNND in NOAA climate regions and EPA ecoregions were often contradictory in both direction and magnitude, with EPA ecoregions more often supporting previously established biological hypotheses and environmental dynamics underlying vector‐borne disease transmission. Using ecological regions to examine the relationships between climate and disease cases can enhance the predictive power of forecasts at various scales, motivating a conceptual shift in large‐scale analyses from geopolitical frameworks to more ecologically meaningful regions. While health data is collected within geopolitical boundaries, environmental disease dynamics are influenced by ecosystem characteristicsFor West Nile virus, correlations between cases and climate were different depending on geopolitical or ecosystem regional groupings of dataWe propose a conceptual shift from analyzing climate and health data at geopolitical boundaries to more ecologically meaningful regions

Introduction: Climate and land use change may cause the geographical range of mosquitoes to expand, shift, or contract, ultimately changing what communities are at risk for contracting mosquito-borne diseases. Across North and South America, mosquitoes from the Aedes and Culex genera are vectors for numerous diseases, including chikungunya, dengue, various equine encephalitis viruses, Saint Louis encephalitis virus, West Nile virus, yellow fever virus, and Zika virus. The goal of our study was to project the geographical distributions of important mosquito vectors across North and South America in response to climate change, which is important to inform public health planning. Methods: We used an ecological niche model and future projections of climate and land use to project the geographical ranges of two Aedes species ( Ae. aegypti, Ae. albopictus ) and seven Culex species ( Cx. erraticus, Cx. nigripalpus, Cx. pipiens, Cx. quinquefasciatus, Cx. restuans, Cx. salinarius, Cx. tarsalis ) over North and South America in response to both a high (Shared Socioeconomic Pathway [SSP] 5, Representative Concentration Pathway [RCP] 8.5) and moderate (SSP2 RCP4.5) climate warming scenario through years 2050 and 2090. Results: For SSP5 RCP8.5, six species ( Ae. aegypti, Ae. albopictus, Cx. erraticus, Cx. nigripalpus, Cx. quinquefasciatus, Cx. restuans ) are projected to expand in geographical range, two species ( Cx. pipiens, Cx. tarsalis ) are projected to shift in geographical range, and one species ( Cx. salinarius ) is projected to nearly remain the same. Five species ( Ae. aegypti, Ae. albopictus, Cx. erraticus, Cx. nigripalpus, Cx. quinquefasciatus ) show the largest increase in high habitat suitability ( >0.5 on a 0 -1 scale) for SSP5 RCP8.5, three species ( Cx. pipiens, Cx. restuans, Cx. tarsalis ) show the largest increase for SSP2 RCP4.5, and one species ( Cx. salinarius ) shows a relatively small decrease in response to both scenarios. Conclusions: We found that all nine species responded resiliently to climate change under both the high and moderate climate warming scenario, suggesting mosquito-borne disease is likely to be a continued threat in response to climate change. The projected geographical ranges can be used to inform disease risk analyses and mitigation strategies in response to climate change. (c) 2024 Published by Elsevier Masson SAS. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

School-age children play a key role in the spread of airborne viruses like influenza due to the prolonged and close contacts they have in school settings. As a result, school closures and other non-pharmaceutical interventions were recommended as the first line of defense in response to the novel coronavirus pandemic (COVID-19). We used an agent-based model that simulates communities across the United States including daycares, primary, and secondary schools to quantify the relative health outcomes of reopening schools for the period of August 15, 2020 to April 11, 2021. Our simulation was carried out in early September 2020 and was based on the latest (at the time) Centers for Disease Control and Prevention (CDC)’s Pandemic Planning Scenarios released in May 2020. We explored different reopening scenarios including virtual learning, in-person school, and several hybrid options that stratify the student population into cohorts in order to reduce exposure and pathogen spread. Scenarios where cohorts of students return to school in non-overlapping formats, which we refer to as hybrid scenarios, resulted in significant decreases in the percentage of symptomatic individuals with COVID-19, by as much as 75%. These hybrid scenarios have only slightly more negative health impacts of COVID-19 compared to implementing a 100% virtual learning scenario. Hybrid scenarios can significantly avert the number of COVID-19 cases at the national scale–approximately between 28 M and 60 M depending on the scenario–over the simulated eight-month period. We found the results of our simulations to be highly dependent on the number of workplaces assumed to be open for in-person business, as well as the initial level of COVID-19 incidence within the simulated community. In an evolving pandemic, while a large proportion of people remain susceptible, reducing the number of students attending school leads to better health outcomes; part-time in-classroom education substantially reduces health risks. [Display omitted] •Here, we stratify the workforce by industry classification so we can quantify the impact of restrictions on businesses.•This study assesses the combined impact of business restrictions and school reopening scenarios on community spread.