Equipa Multidisciplinar de Profissionais de Saúde, Docentes e Investigadores Nacionais

Influence of population density and access to sanitation on Covid-19 inMozambique

Edgar Manuel Cambaza 1 *

ABSTRACT In 2020, as COVID-19 spread worldwide, prestigious entities published faulty predictions about the level of dissemination,especially when describing African countries and others with “weak healthcare systems.” How could the best fall so short,even when using well-known epidemiological variables to predict the behavior of a hygiene-related malady? It might havebeen due to insufficient data since COVID-19 was a novelty, still poorly understood. The current study aimed to analyze howtwo variables – population density and percentage of people with access to improved sanitation – affected the number ofconfirmed COVID-19 cases in Mozambique by February 2021, almost one year since the first case in the country. All datawere publicly available: population density in Census 2017, access to sanitation in the Mozambique Public Expenditure Review2014, and the number of COVID- 19 cases in the Ministry of Health’s COVID -19 daily bulletin (no. 332). JASP 0.13.1.0 allowedcorrelating all variables, and Microsoft Excel™ was chosen to perform fitting analysis to model the algebraic relationshipbetween the number of cases and the other variables. The cases showed a positive correlation (r = 0.663) with density, andtheir relationship was consistent with a cubic function. Sanitation coverage also showed a positive correlation (r = 0.679), butthe most straightforward algebraic representation was a quadratic function. The impact of population density on the numberof COVID-19 cases was intuitive, but the logic points towards the highest number of cases where sanitation facilities lackedthe most. Thus, the influence of other factors outweighed the effect of sanitation, or people tend to be careless before thesense of security where the sanitation is better. Nevertheless, these findings can support predictions and decision-making,and the population needs to abide by the Government’s recommendations.

Keywords : Population density; Sanitation; Covid-19; Mozambique

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1- Departamento de Ciências sa Saúde, Insituto Superior de Ciências e Educação à Distância, Moçambique. Orcid: 0000-0002-0592-7812 *- Autor correspondente. Email: ecambaza@isced.ac.mz Doi: https://doi.org/10.54283/RACSaude.2789-2832.v2n1_2021.p3-8 Received: 01 de março de 2021 / Accepted : 15 de Junho de 2021 / Published : 30 de Junho de 2021

INTRODUCTION

As COVID-19 entered African countries, there were uncertainties due to lack of data, combined withmisinformation and infodemic. Therefore, it was hard to deliver clear-cut accurate analyses of the factorsaffecting the pandemic. Some variables intuitively affected the dissemination of COVID-19, as the article“African miracle” 1 mentioned in June 2020. However, there were by then only three months of data to make anysense of the evidence. A “usual suspect” was population density because the logic points to a higher risk ofCOVID-19 the more people inhabits a particular area. On the other hand, in the same article, I said predictinga tragedy in Africa solely based on the population’s poor hygiene and sanitation access was anoversimplification. Nevertheless, I never meant that poor sanitation would not affect the dissemination ofCOVID-19 because the disease is hygiene-related.The Mozambican Government reported the first confirmed case of COVID-19 on 23 March 2020. By now, ithas been approximately one year, and it seems to be an excellent time to make some sense of the dataavailable. For instance, it is reasonable to assume that COVID-19 would take some time to develop adistribution pattern according to the population density, in part as a function of the virus reproduction rate (R0).Furthermore, there is an overwhelming body of evidence supporting the population density’ s impact ondisseminating COVID-19 2-4 , besides the logic and common sense. Arnaldo et al. 5 published an attempt topredict the risk of COVID-19 in all Mozambique districts based based on factors, including population density.However, they did not provide tangible evidence of the association between the variables in the country, thuswriting a merely speculative analysis.

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