Intraregional propagation of Covid-19 cases in Pará, Brazil: assessment of isolation regime to lockdown

Spatial and socioeconomic patterns of COVID-19 in transition zones between municipalities in eastern Amazonia

Background

Herein, we assess hospitalizations and deaths from COVID-19 in Amazonian municipalities, taking into account regional, demographic, and socioeconomic peculiarities. Public data from 2020 and 2021 of 52,082 cases of COVID-19 were analyzed in R Program.

Methods

We examined the interaction of mortality, hospitalization, and fatality rates of COVID-19, considering socioeconomic, demographic, and geographic variables. We measured the spatial autocorrelation of the rates associated with the variables POP, GDP, Residents, HDI, and GINI. The spatial patterns found show distinctly affected sectors and COVID-19 transition zones between municipalities.

Results

We detected higher mortality rates in territories with greater social and environmental vulnerability. Analysis of the mortality rate indicates that all the socioeconomic variables tested are associated with this variable, but their effects interact in a complex way. The municipalities with higher numbers of residents per household and Gini coefficients had higher fatality rates, and municipalities with a higher GDP were more associated with higher hospitalization and mortality rates. Furthermore, the five socioeconomic indices included in multiple regressions analyzing mortality and hospitalization rates exhibited significant interaction effects. However, no significant interaction effects were observed in the fatality rate analyses.

Conclusion

Spatial analyses showed that none of the 144 municipalities studied had high overlapping rates of mortality, hospitalization, and fatality rates for COVID-19 in the same municipality. We recommend further studies in the transition zones, considering the municipalities of Floresta do Araguaia, Mãe do Rio, and Redenção for mortality, Barcarena, Capitão Poço, and Redenção for hospitalization, and Cumaru do Norte and Pau D'Arco for fatality, in order to understand the health dynamics of each territory. The most affected areas are located near the border with the state of Amazonas. We recommend the adoption of personalized strategies for Amazonian municipalities when targeting future public health events.

A meta-analysis result: Uneven influences of season, geo-spatial scale and latitude on relationship between meteorological factors and the COVID-19 transmission

Meteorological factors have been confirmed to affect the COVID-19 transmission, but current studied conclusions varied greatly. The underlying causes of the variance remain unclear. Here, we proposed two scientific questions: (1) whether meteorological factors have a consistent influence on virus transmission after combining all the data from the studies; (2) whether the impact of meteorological factors on the COVID-19 transmission can be influenced by season, geospatial scale and latitude. We employed a meta-analysis to address these two questions using results from 2813 published articles. Our results showed that, the influence of meteorological factors on the newly-confirmed COVID-19 cases varied greatly among existing studies, and no consistent conclusion can be drawn. After grouping outbreak time into cold and warm seasons, we found daily maximum and daily minimum temperatures have significant positive influences on the newly-confirmed COVID-19 cases in cold season, while significant negative influences in warm season. After dividing the scope of the outbreak into national and urban scales, relative humidity significantly inhibited the COVID-19 transmission at the national scale, but no effect on the urban scale. The negative impact of relative humidity, and the positive impacts of maximum temperatures and wind speed on the newly-confirmed COVID-19 cases increased with latitude. The relationship of maximum and minimum temperatures with the newly-confirmed COVID-19 cases were more susceptible to season, while relative humidity's relationship was more affected by latitude and geospatial scale. Our results suggested that relationship between meteorological factors and the COVID-19 transmission can be affected by season, geospatial scale and latitude. A rise in temperature would promote virus transmission in cold seasons. We suggested that the formulation and implementation of epidemic prevention and control should mainly refer to studies at the urban scale. The control measures should be developed according to local meteorological properties for individual city.