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Pan Afr Med J ; 37: 293, 2020.
Artigo em Inglês | MEDLINE | ID: mdl-33654515

RESUMO

INTRODUCTION: continuous assessment of healthcare resources during the COVID-19 pandemic will help in proper planning and to prevent an overwhelming of the Nigerian healthcare system. In this study, we aim to predict the effect of COVID-19 on hospital resources in Nigeria. METHODS: we adopted a previously published discrete-time, individual-level, health-state transition model of symptomatic COVID-19 patients to the Nigerian healthcare system and COVID-19 epidemiology in Nigeria by September 2020. We simulated different combined scenarios of epidemic trajectories and acute care capacity. Primary outcomes included the expected cumulative number of cases, days until depletion resources and the number of deaths associated with resource constraints. Outcomes were predicted over a 60-day time horizon. RESULTS: in our best-case epidemic trajectory, which implies successful implementation of public health measures to control COVID-19 spread, assuming all three resource scenarios, hospital resources would not be expended within the 60-days time horizon. In our worst-case epidemic trajectory, assuming conservative resource scenario, only ventilated ICU beds would be depleted after 39 days and 16 patients were projected to die while waiting for ventilated ICU bed. Acute care resources were only sufficient in the three epidemic trajectory scenarios when combined with a substantial increase in healthcare resources. CONCLUSION: substantial increase in hospital resources is required to manage the COVID-19 pandemic in Nigeria, even as the infection growth rate declines. Given Nigeria's limited health resources, it is imperative to focus on maintaining aggressive public health measures as well as increasing hospital resources to reduce COVID-19 transmission further.


Assuntos
COVID-19/terapia , Atenção à Saúde/organização & administração , Recursos em Saúde/estatística & dados numéricos , Hospitais/estatística & dados numéricos , Cuidados Críticos/estatística & dados numéricos , Atenção à Saúde/estatística & dados numéricos , Humanos , Unidades de Terapia Intensiva/organização & administração , Unidades de Terapia Intensiva/estatística & dados numéricos , Modelos Teóricos , Nigéria , Fatores de Tempo
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