A Vulnerability Analysis for the Management of and Response to the COVID-19 Epidemic in the Second Most Populous State in Brazil

Abstract

The COVID-19 pandemic has the potential to affect all individuals, however in a heterogeneous way. In this sense, identifying specificities of each location is essential to minimize the damage caused by the disease. Therefore, the aim of this research was to assess the vulnerability of 853 municipalities in the second most populous state in Brazil, Minas Gerais (MG), in order to direct public policies. An epidemiological study was carried out based on Multi-Criteria Decision Analysis (MCDA) using indicators with some relation to the process of illness and death caused by COVID-19. The indicators were selected by a literature search and categorized into: demographic, social, economic, health infrastructure, population at risk and epidemiological. The variables were collected in Brazilian government databases at the municipal level and evaluated according to MCDA, through the Program to Support Decision Making based on Indicators (PRADIN). Based on this approach, the study performed simulations by category of indicators and a general simulation that allowed to divide the municipalities into groups of 1–5, with 1 being the least vulnerable and 5 being the most vulnerable. The groupings of municipalities were exposed in their respective mesoregions of MG in a thematic map, using the software Tabwin 32. The results revealed that the mesoregion of Norte de Minas stands out with more than 40% of its municipalities belonging to group 5, according to economic, social and health infrastructure indicators. Similarly, the Jequitinhonha mesoregion exhibited almost 60% of the municipalities in this group for economic and health infrastructure indicators. For demographic and epidemiological criteria, the Metropolitana de Belo Horizonte was the most vulnerable mesoregion, with 42.9 and 26.7% of the municipalities in group 5, respectively. Considering the presence of a population at risk, Zona da Mata reported 42.3% of the municipalities in the most vulnerable group. In the joint analysis of data, the Jequitinhonha, Vale do Mucuri and Vale do Rio Doce mesoregions were the most vulnerable in the state of MG. Thus, through the outlined profile, the present study proved how socioeconomic diversity affects the vulnerability of the municipalities to face COVID-19 outbreak, highlighting the need for interventions directed to each reality.

Epidemiological Monitoring of COVID-19 in a Brazilian City: The Interface between the Economic Policies, Commercial Behavior, and Pandemic Control

“…It is worth mentioning that the state of Minas Gerais was among the 10 federative units in the country with the highest rates of contamination [22]. Findings in the literature demonstrate a possible ineffectiveness of social isolation measures in some regions of Minas Gerais, such as the Jequitinhonha and Norte de Minas mesoregions, where economically disadvantaged people are more likely to live in housing with a high number of individuals, which, therefore, favor the risk of infection [23]. In addition to this social vulnerability, other factors, such as those of an economic and climatic nature, as well as the flow of transport, contribute to the understanding of the spread of the virus in this state [24].…”

Pandemic vulnerability index of US cities: A hybrid knowledge-based and data-driven approach

“…Fragile socioeconomic conditions render people vulnerable to extreme conditions, and therefore also expose them more directly to the COVID-19 pandemic. As presented in Table 2 , a total of 10 social and economic variables are selected in this theme based on their relation to community vulnerability in the extant literature ( Campos et al, 2021 , Coven and Gupta, 2020 , Fortaleza et al, 2020 , Hossain et al, 2021 , Kashem et al, 2021 , Snyder and Parks, 2020 ). In the US, people’s poverty level is measured based on household or family income.…”

“…They found that the metropolitan land area, population density, how populous a place is, its Human Development Index (HDI), and its Gini index (i.e., income inequality) have a positive association with COVID-19 prevalence ( Fortaleza et al, 2020 ). Similarly, another study ( Campos, Aratani, Cabral, Limongi, & Oliveira, 2021 ) from Brazil assessed vulnerabilities of 853 cities and concluded that high urbanization and population density, inadequate sanitation, high illiteracy, high Gini index, low HDI and household income, weak healthcare infrastructure, and a high number of people with underlying health conditions increased urban vulnerabilities to COVID-19 infection. Pourghasemi et al.…”

A district-level vulnerability assessment of next COVID-19 variant (Omicron BA.2) in Uttarakhand using quantitative SWOT analysis

“…For better planning, it is crucial to find out areas that need special attention (Nisari et al, 2016). This purpose is served by conducting a vulnerability assessment done on various grounds using statistical methods (Nikolopoulos et al, 2021 ), vulnerability indices (Tuite et al, 2020 ; Campos et al, 2021 ) and geospatial techniques (Ali et al, 2021 ; Parvin et al, 2021 ). Researchers have also tried to assess the impact and modelled the vulnerabilities of COVID-19 on different part of the society (Daras at al., 2021) and various economic classes (Bidisha et al, 2021 ; Rahman et al, 2021 ).…”

“…The PCA has been utilised for modelling socio-economic as well as climatic vulnerability of COVID-19 (Salvacian, 2022). Multi-criteria decision-making (MCDM) was adopted for vulnerability assessments of Brazil (Campos et al, 2021 ) and Argentina (Özkaya and Özkaya, 2022 ). GIS and overlay techniques have been highly useful in the assessment of COVID-19.…”