03147nas a2200325 4500000000100000008004100001260004400042653002400086653001300110653001700123653001200140653003000152653003100182100001200213700001500225700002300240700001600263700002100279700002400300700001500324700001800339700001700357700001200374245012400386856002700510300000900537490000700546520225400553022001402807 2023 d bSpringer Science and Business Media LLC10aInfectious Diseases10aCovid-1910aTuberculosis10aLeprosy10aGeographical distribution10aSocioeconomic risk factors1 aTaal AT1 aBarreto JG1 aSantos de Sousa GD1 ada Rocha AM1 aLima Ferreira NN1 aMenezes da Silva JA1 aHinders DC1 avan Brakel WH1 aRichardus JH1 aBlok DJ00aThe geographical distribution and socioeconomic risk factors of COVID-19, tuberculosis and leprosy in Fortaleza, Brazil uhttps://rdcu.be/doVGN a1-100 v233 a
Background: Fortaleza (Brazil) is high endemic for coronavirus disease 2019 (COVID-19), tuberculosis (TB) and leprosy. These three diseases share respiratory droplets through coughing or sneezing as the main mode of transmission but differ in incubation time, with COVID-19 having a short and leprosy a long incubation time. Consequently, contacts of a patient are at higher risk of infection and developing these diseases. There might be scope for combined preventive measures, but a better understanding of the geographical distribution and relevant socioeconomic risk factors of the three diseases is needed first. This study aims to describe the geographic distribution of COVID-19, TB and leprosy incidence and to identify common socioeconomic risk factors.
Methods: The total number of new cases of COVID-19, TB and leprosy, as well as socioeconomic and demographic variables, were retrieved from official registers. The geographical distribution of COVID-19, TB and leprosy rates per neighbourhood was visualised in Quantum GIS, and spatial autocorrelation was measured with Moran’s I in GeoDa. A spatial regression model was applied to understand the association between COVID-19, TB, leprosy rates, and socioeconomic factors.
Results: COVID-19 and TB showed a more homogenous distribution, whereas leprosy is located more in the south and west of Fortaleza. One neighbourhood (Pedras) in the southeast was identified as high endemic for all three diseases. Literacy was a socioeconomic risk factor for all three diseases: a high literacy rate increases the risk of COVID-19, and a low literacy rate (i.e., illiteracy) increases the risk of TB and leprosy. In addition, high income was associated with COVID-19, while low income with TB.
Conclusions: Despite the similar mode of transmission, COVID-19, TB and leprosy show a different distribution of cases in Fortaleza. In addition, associated risk factors are related to wealth in COVID-19 and to poverty in TB and leprosy. These findings may support policymakers in developing (partially combined) primary and secondary prevention considering the efficient use of resources.
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