Impact of Prioritizing Elderly and High-risk Individuals During COVID-19 Vaccine Allocation (preprint)

Background: The prioritization of vaccine eligibility for different subpopulations is an important decision to curb spread and severe outcomes of epidemic infectious diseases for which vaccines become available. Using COVID-19 as a prototype, this study evaluates the public health impact of various vaccine prioritization schemes of elderly and high-risk individuals with different vaccination start dates and rollout speeds. MethodsAn agent-based simulation model was adapted and used to project the number of infections, hospitalizations, and deaths under various vaccination start dates, rollout speeds, and prioritization schemes, including (A)no prioritization, (B)two-staged prioritization of elderly population, and (C)multi-staged prioritization of elderly and then high-risk population. The study period was February 18 th , 2020 –June 1 st , 2021, and the state of Georgia was used as a case study. ResultsThe relative effectiveness of the prioritization schemes depends on the outcome considered, as well as the vaccination start date, prioritized subpopulations, and rollout speed. Having no prioritization results in the fewest infections and hospitalizations in most scenarios; however, it yields the highest number of deaths. Prioritizing the elderly and then high-risk individuals results in the fewest overall and high-risk deaths in most scenarios. ConclusionsHaving no vaccine prioritization, i.e., opening vaccination to every adult regardless of age, simplifies vaccine rollout and reduces the infection spread but results in a higher number of deaths, especially among the elderly and high-risk populations. Prioritizing the elderly, then high-risk patients, as opposed to prioritizing only the elderly provides benefit regarding severe outcomes; however, such assumed benefits need to be counterbalanced with challenges in communicating eligibility and criteria and in distributing vaccines effectively and equitably which could result in suboptimal vaccine uptake and coverage, including among people within subpopulations at disproportionate risk of illness, hospitalization and death, of particular concern during periods of high incidence, severe disease, and death.

Evaluation of individual and ensemble probabilistic forecasts of COVID-19 mortality in the US (preprint)

Short-term probabilistic forecasts of the trajectory of the COVID-19 pandemic in the United States have served as a visible and important communication channel between the scientific modeling community and both the general public and decision-makers. Forecasting models provide specific, quantitative, and evaluable predictions that inform short-term decisions such as healthcare staffing needs, school closures, and allocation of medical supplies. In 2020, the COVID-19 Forecast Hub (https://covid19forecasthub.org/) collected, disseminated, and synthesized hundreds of thousands of specific predictions from more than 50 different academic, industry, and independent research groups. This manuscript systematically evaluates 23 models that regularly submitted forecasts of reported weekly incident COVID-19 mortality counts in the US at the state and national level. One of these models was a multi-model ensemble that combined all available forecasts each week. The performance of individual models showed high variability across time, geospatial units, and forecast horizons. Half of the models evaluated showed better accuracy than a naive baseline model. In combining the forecasts from all teams, the ensemble showed the best overall probabilistic accuracy of any model. Forecast accuracy degraded as models made predictions farther into the future, with probabilistic accuracy at a 20-week horizon more than 5 times worse than when predicting at a 1-week horizon. This project underscores the role that collaboration and active coordination between governmental public health agencies, academic modeling teams, and industry partners can play in developing modern modeling capabilities to support local, state, and federal response to outbreaks. f

Homebound by COVID19: The Benefits and Consequences of Non-Pharmaceutical Intervention Strategies (preprint)

Background: . Recent research has been conducted by various countries and regions on the impact of non-pharmaceutical interventions (NPIs) on reducing the spread of COVID19. This study evaluates the tradeoffs between potential benefits (e.g., reduction in infection spread and deaths) of NPIs for COVID19 and being homebound (i.e., refraining from interactions outside of the household). Methods: . An agent-based simulation model, which captures the natural history of the disease at the individual level, and the infection spread via a contact network assuming heterogeneous population mixing in households, peer groups (workplaces, schools), and communities, is adapted to project the disease spread and estimate the number of homebound people and person-days under multiple scenarios, including combinations of shelter-in-place, voluntary quarantine, and school closure in Georgia from March 1 to September 1, 2020. Results: . Compared to no intervention, under voluntary quarantine, voluntary quarantine with school closure, and shelter-in-place with school closure scenarios 4.5, 23.1, and 200+ homebound adult-days were required to prevent one infection, with the maximum number of adults homebound on a given day in the range of 119K-248K, 465K-499K, 5,388K-5,389K, respectively. Compared to no intervention, school closure only reduced the percentage of the population infected by less than 16% while more than doubling the peak number of adults homebound. Conclusions: . Voluntary quarantine combined with school closure significantly reduced the number of infections and deaths with a considerably smaller number of homebound person-days compared to shelter-in-place.

Evaluating Scenarios for School Reopening Under COVID19 (preprint)

Background: Thousands of school systems have been struggling with the decisions about how to safely and effectively deliver education during the fall semester of 2020, amid the COVID19 pandemic. This study evaluates the public health impact of various school reopening scenarios (when, and how to return in-person instruction) on the spread of COVID19. Methods: : An agent-based simulation model was adapted and used to project the number of infections and deaths under multiple school reopening dates and scenarios, including different cohorts receiving in-person instruction on alternating days, only younger children returning to in-person instruction, regular schedule (all students receiving in-person instruction), and school closure (all students receiving online instruction). The study period was February 18 th -November 24 th , 2020 and the state of Georgia was used as a case study. Results: : Across all scenarios, the number of COVID19-related deaths ranged from approximately 17 to 22 thousand during the study period, and on the peak day, the number of new infections ranged from 43 to 68 thousand. An alternating school day schedule performed: (i) almost as well as keeping schools closed, with the infection attack rate ranging from 38.5% to 39.8% compared to that of 37.7% under school closure; (ii) slightly better than only allowing children 10 years or younger to return to in-person instruction. Delaying the reopening of schools had a minimal impact on reducing infections and deaths under most scenarios. Conclusions: : Reopening schools following a regular schedule, i.e., all children returning to school without strict public health measures, would have serious negative public health consequences. The alternating school day schedule, especially if offered as an option to families and teachers who prefer to opt in, provides a good balance in reducing the infection spread compared to the regular schedule, while ensuring access to in-person education.

Evaluating Scenarios for School Reopening under COVID19 (preprint)

Thousands of school systems have been struggling with the decisions about how to safely and effectively deliver education during the fall semester of 2020, amid the COVID19 pandemic. The objective of this study is to evaluate the public health impact of reopening schools on the spread of COVID19. An agent-based simulation model was adapted and used to project the number of infections and deaths under multiple school reopening dates and scenarios, including different cohorts receiving in-person instruction on alternating days, only younger children returning to in-person instruction, regular schedule (all students receiving in-person instruction), and school closure (all students receiving online instruction). The study period was February 18th-November 24th, 2020 and the state of Georgia was used as a case study. Across all scenarios, the number of COVID19-related deaths ranged from approximately 17 to 22 thousand during the study period, and on the peak day, the number of new infections ranged from 43 to 68 thousand. An alternating school day schedule performed: (i) almost as well as keeping schools closed, with the infection attack rate ranging from 38.5% to 39.8% compared to that of 37.7% under school closure; (ii) slightly better than only allowing children 10 years or younger to return to in-person instruction. Delaying the reopening of schools had a minimal impact on reducing infections and deaths under most scenarios.

Homebound by COVID19: The Benefits and Consequences of Non-Pharmaceutical Intervention Strategies (preprint)

ObjectivesTo evaluate the tradeoffs between potential benefits (e.g., reduction in infection spread and deaths) of non-pharmaceutical interventions for COVID19 and being homebound (i.e., refraining from community/workplace interactions). MethodsAn agent-based simulation model to project the disease spread and estimate the number of homebound people and person-days under multiple scenarios, including combinations of shelter-in- place, voluntary quarantine, and school closure in Georgia from March 1 to September 1, 2020. ResultsCompared to no intervention, under voluntary quarantine, voluntary quarantine with school closure, and shelter-in-place with school closure scenarios 3.43, 19.8, and 200+ homebound adult-days were required to prevent one infection, with the maximum number of adults homebound on a given day in the range of 121K-268K, 522K-567K, 5,377K-5,380K, respectively. ConclusionsVoluntary quarantine combined with school closure significantly reduced the number of infections and deaths with a considerably smaller number of homebound person-days compared to shelter-in-place. Three-question Summary BoxO_LIWhat is the current understanding of this subject? Recent research has been conducted by various countries and regions on the impact of non-pharmaceutical interventions (NPIs) on reducing the spread of COVID19. C_LIO_LIWhat does this report add to the literature? Our report assessed which intervention strategies provided the best results in terms of both reducing infection outcomes (cases, deaths, etc.) and minimizing their social and economic effects (e.g., number of people homebound, providing childcare, etc.). C_LIO_LIWhat are the implications for public health practice? Voluntary quarantine proved to be the most beneficial in terms of reducing infections and deaths compared to the number of people who were homebound. C_LI

The Impact of Social Distancing on COVID19 Spread: State of Georgia Case Study (preprint)

ImportanceAs the COVID19 spread in the US continues to grow, local and state officials face difficult decisions about when and how to transition to a "new normal." ObjectiveProject the number of COVID19 infections and resulting severe outcomes, and the need for hospital capacity under social distancing, particularly, shelter-in-place and voluntary quarantine. DesignWe developed an agent-based simulation model to project the infection spread. We populated the model using COVID19-specific parameters for the natural history of the disease and data from Georgia on agents interactions and demographics. SettingThe simulation study covered a six-month period, testing different social distancing scenarios, including baselines (no-intervention or school closure only) and combinations of shelter-in-place and voluntary quarantine with different timelines and compliance levels. The outcomes are compared at the state and community levels. Main OutcomesThe number and percentage of cumulative and daily new and symptomatic and asymptomatic infections, hospitalizations, and deaths; COVID19-related demand for hospital beds, ICU beds, and ventilators. ResultsThe combined intervention of shelter-in-place followed by voluntary quarantine reduced peak infections from 180,000 under no intervention and 120,000 under school closure, respectively, to below 80,000, and delayed the peak from April to June or later. Increasing shelter-in-place duration from four to five weeks yielded 3-14% and 4-6% decrease in cumulative infection and fatality rates, respectively. Regardless of the shelter-in-place duration, increasing voluntary quarantine compliance decreased daily new infections from almost 80,000 to 50,000, and decreased cumulative infection rate by 50%. The total number of fatalities ranged from 6,150 to 17,900 under different scenarios. Peak infection date varied across scenarios and counties; on average, increasing shelter-in-place duration delayed the peak day by 7 days across counties. The peak percentage is similar across rural and urban counties. Region D is estimated to have the highest COVID19-related healthcare needs with 7,357 hospital beds, 1,141 ICU beds, and 558 ventilators. Conclusions and RelevanceShelter-in-place followed by voluntary quarantine substantially reduce COVID19 infections, healthcare resource needs, and severe outcomes; delay the peak; and enable better preparedness. Time of the peak is projected to vary across locations, enabling reallocation of health system capacity. KEY POINTSO_ST_ABSQuestionC_ST_ABSHow social distancing strategies impact the spread of COVID19? FindingsExtending shelter-in-place by one week delays the peak by about 8 days but it does not significantly reduce the peak. High compliance with voluntary quarantine following shelter-in-place reduces the peak by 40% in Georgia. MeaningThere needs to be a very strong public messaging about social distancing when shelter-in-place is lifted, to achieve a better match between healthcare capacity and demand, considering different peak times across the communities.