Forecasting COVID-19 Pandemic in Mozambique and Estimating Possible Scenarios

TL;DR

This study uses a simple SEIR model to forecast COVID-19 scenarios in Mozambique, analyzing policy impacts and estimating key epidemiological parameters to inform pandemic management.

Contribution

It provides specific modeling and scenario analysis for Mozambique, a less-studied African country, using a tailored SEIR approach and policy impact evaluation.

Findings

Reproduction number Rt ranges from 1.11 to 1.48.

Growth rate g is between 0.22 and 0.27.

Lockdowns could reduce infection peaks by up to 36%.

Abstract

COVID-19 is now the largest pandemic crisis of this century, with over 16 million registered cases worldwide. African countries have now begun registering an increasing number of cases, yet, not many models developed focus in specific African countries. In our study we use a simple SEIR model to evaluate and predict future scenarios regarding the pandemic crisis in Mozambique. We compare the effect of different policies on the infection curve and estimate epidemiological parameters such as the current infection reproduction number Rt and the growth rate g. We have found a low value for Rt, ranging from 1.11 to 1.48 and a positive growth rate, between g = 0.22 to 0.27. Our simulations also suggest that a lockdown shows potential for reducing the infection peak height in 28%, on average, ranging from 20 to 36%.