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Protecting people in long-term care facilities from COVID-19 by routine testing of employees - a modeling approach

Pierre Marie Ngougoue N. † , H. Christian Jr. Tsoungui Obama † , Nessma Adil M. Y. † , Looli Alawam N. ∗ , Gideon A. Ngwa ◦ , Miranda Teboh-Ewungkem • , Kristan A. Schneider †

† Hochschule Mittweida, University of Applied Sciences, ∗ African Institute for Mathematical Sciences Cameroon, ◦ University of Buea, • Lehigh University.

The COVID-19 pandemic with its high infectiousness is a public health emergency of international concern, particularly threatening the lives of senior citizens, that forced policymakers to implement draconic control interventions affecting the global economy and restricting civil rights. With borders closed many countries face the problem of efficiently reacting to the pandemic due to inaccurate case detection and a potentially high number of unreported cases. With data being initially sparse and heavily biased, health management decisions need to be guided by model predictions. The CDC identified people living in long-term care facilities (LTCF) as a high-risk group. The protection of such citizens against the COVID-19 is a priority in disease management. This requires regular testing of staff working in LTCFs. With a limited capacity of reliable PCR tests, monitoring LTCFs needs to be carefully optimized. We present a predictive model, that is an extension of the pandemic preparedness tool CovidSIM Version 1.1 (http://covidsim.eu/) that considers the interactions between three groups: the general population, the risk group living in LTCFs, and the LTCF staff. We study the effect of routine testing and isolation of LTCF staff as a measure to protect the risk group.  The model helps to optimize the testing schemes of LTCF staff to efficiently protect the risk group. The model allows contrasting the economic gain of protecting the risk groups against the costs for regular COVID-19 testing. We present simulation results obtained by using the software Python roughly reflecting the situation in the Federal Republic of Germany.