Group 1: Workplace Absenteeism due to COVID-19 and Influenza: A Mathematical Model

Abstract: The continual distress of COVID-19 can not be overemphasized. The disease’s economic and social costs are alarming, with recent attributed economic loss amounting to billions of dollars globally. This economic loss is partly driven by workplace absenteeism due to the disease; influenza is believed a culprit in reinforcing this phenomenon as it exists in the population concurrently with COVID-19 during the flu season---their joint infection may heighten the economic loss due to their impact on workplace absenteeism. This project aims at quantifying the joint impact of these diseases on workplace absenteeism via a mathematical compartmental disease model with vaccination framework. We establish that appropriate testing and vaccination of both diseases have a tremendous impact on workplace absenteeism, thus we recommend that testing should be a major component of the ongoing vaccination program. Also, the study shows that the population has the added benefit of the positive effect of influenza vaccination on COVID-19 transmission. Increasing the testing capacity beyond a particular threshold may not yield optimal results in regards to reducing absenteeism. We are of the view that health policy makers should adopt the above findings in their decision.

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Group 2: Assessing Alternative Vaccination Strategies and their Epidemiological and Economic Impacts: A Modelling Study

Abstract: Governments across the globe are taking multiple measures to respond to the urgent care needs of those impacted by COVID-19 while at the same time trying to reduce the burden on society and the economy. There is a dire need to put forward an effective vaccination program to reduce the disease prevalence within the shortest possible time. Strategies implemented come with their associated costs—the economic and social costs. This study proposes three possible vaccination strategies to reduce the disease prevalence based on different national conditions. We then quantified the economic and social costs associated with the proposed strategies by developing mathematical disease models on COVID-19 that incorporate these vaccination strategies. The strategies proposed are applicable to both developed and developing countries. Discussion of policy recommendation is also provided by comparing the three vaccination strategies to investigate the best strategy to balance the lower vaccine uses and social costs.

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Group 3: Wastewater Testing as an Early Warning Tool for SARS-CoV-2 Outbreaks

Abstract: There is a great need in understanding the entire potential of using wastewater surveillance (WWS) as a tool in the context of SARS-CoV-2 to assess and predict infection outbreaks. WWS has the advantage over several typically utilized surveillance system sources, given that a broader range of infected individuals will contribute to the virus signal in wastewater. Dynamic models typically rely on surveillance data that is substantially delayed from the first onset of infection, prone to under-reporting and under-ascertainment. In this light, we aimed to investigate the usage of WWS data, which overcomes several of these limitations, as an early warning source and further to understand the conditions under which WWS could be used for public health purposes in the context of COVID-19. We utilized multi-source data across 26 cities in Wyoming, USA and: 1. performed cross-correlation analysis to explore time delays in estimated wastewater virus concentration and reported cases of COVID-19; 2. developed a transmission dynamics model (SEAIRDW) which included a compartment for the SARS-CoV-2 virus concentration in wastewater and fit the model to confirmed cases and WWS data at the city-level. We demonstrate WWS as an early warning tool for the city of Laramie in Albany County, Wyoming, USA, as the transmission dynamics model (SEAIRDW) captured the qualitative behavior of the observable variables (reported cases, virus concentration in wastewater). Prediction of absolute case counts could be improved with further model tuning. Our analysis indicates that the geographic alignment of the catchment area of case surveillance and WWS data is a key factor in the utilization of WWS. Further investigation is needed; however, the establishment of a transmission dynamics model which produces observable system states may be a key first step in producing SARS-CoV-2 outbreak trajectories.