Modeling the Climatic Suitability of COVID-19 Cases in Brazil

Studies have shown that climate may affect the distribution of coronavirus disease (COVID-19) and its incidence and fatality rates. Here, we applied an ensemble niche modeling approach to project the climatic suitability of COVID-19 cases in Brazil. We estimated the cumulative incidence, mortality rate, and fatality rate of COVID-19 between 2020 and 2021. Seven statistical algorithms (MAXENT, MARS, RF, FDA, CTA, GAM, and GLM) were selected to model the climate suitability for COVID-19 cases from diverse climate data, including temperature, precipitation, and humidity. The annual temperature range and precipitation seasonality showed a relatively high contribution to the models, partially explaining the distribution of COVID-19 cases in Brazil based on the climatic suitability of the territory. We observed a high probability of climatic suitability for high incidence in the North and South regions and a high probability of mortality and fatality rates in the Midwest and Southeast regions. Despite the social, viral, and human aspects regulating COVID-19 cases and death distribution, we suggest that climate may play an important role as a co-factor in the spread of cases. In Brazil, there are regions with a high probability that climatic suitability will contribute to the high incidence and fatality rates of COVID-19 in 2020 and 2021.

Medienart:

E-Artikel

Erscheinungsjahr:

2023

Erschienen:

2023

Enthalten in:

Zur Gesamtaufnahme - volume:8

Enthalten in:

Tropical medicine and infectious disease - 8(2023), 4 vom: 29. März

Sprache:

Englisch

Beteiligte Personen:

Neves, Jéssica Milena Moura [VerfasserIn]
Belo, Vinicius Silva [VerfasserIn]
Catita, Cristina Maria Souza [VerfasserIn]
de Oliveira, Beatriz Fátima Alves [VerfasserIn]
Horta, Marco Aurelio Pereira [VerfasserIn]

Links:

Volltext

Themen:

Climate
Coronavirus disease-19
Humidity
Journal Article
Precipitation
Temperature

Anmerkungen:

Date Revised 30.04.2023

published: Electronic

Citation Status PubMed-not-MEDLINE

doi:

10.3390/tropicalmed8040198

funding:

Förderinstitution / Projekttitel:

PPN (Katalog-ID):

NLM356079082