Leptospirosis and its spatial and temporal relations with natural disasters in six municipalities of Santa Catarina, Brazil, from 2000 to 2016

Abstract

Leptospirosis is a serious bacterial infection that occurs worldwide, with fatality rate of up to 40% in the most severe cases. The number of cases peaks during the rainy season and may reach epidemic proportions in the event of flooding. It is possible that people living in areas affected by natural disasters are at greater risk of contracting the disease. The aim of this study was to identify clusters of relatively higher risk for leptospirosis occurrence, both in space and time, in six municipalities of Santa Catarina, Brazil, which had the highest incidence of the disease between 2000 and 2016, and to evaluate if these clusters coincide with the occurrence of natural disasters. The cases were geocoded with the geographic coordinates of patients’ home addresses, and the analysis was performed using SaTScan software. The areas mapped as being at risk for hydrological and mass movements were compared with the locations of detected leptospirosis clusters. The disease was more common in men and in the age group from 15 to 69 years. In the scan statistics performed, only space-time showed significant results. Clusters were detected in all municipalities in 2008, when natural disasters preceded by heavy rainfall occurred. One of the municipalities also had clusters in 2011. In these clusters, most of the cases lived in urban areas and areas at risk for experiencing natural disasters. The interaction between time (time of disaster occurrence) and space (areas at risk of experiencing natural disasters) were the determining factors affecting cluster formation.

Clinical profile, management and outcome of patients with leptospirosis during the times of COVID-19 pandemic: A prospective study from a tertiary care centre in South India

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Determining the spatial distribution of environmental and socio-economic suitability for human leptospirosis in the face of limited epidemiological data

“… Suitability scores may vary over time given that variable spatio-temporal patterns of human leptospirosis incidence have been widely reported (e.g. [ 103 , 104 ]). In Argentina, the highest incidence rates of human leptospirosis were recorded in seasons with warm and moderate temperatures (summer and autumn) [ 26 , 92 , 105 ].…”

Spatio-temporal epidemiology of emergency medical requests in a large urban area. A scan-statistic approach

“…The descriptive maps show the spatial pattern of EMS requests during each time interval, but to identify the high-risk (hotspots) areas of EMS requests by time, we needed to add scan statistics introduced in health sciences by Naus (1965) with spatial and temporal extensions introduced by Kulldorff (1997). These techniques can identify spatial, temporal and space-time clustering as used by (De Carvalho et al, 2020;Punyapornwithaya et al, 2020;Silva et al, 2020). In Kulldorff's scan statistics, the first step is to determine a congruous probability model of the data and compute the likelihood ratio for each scan window.…”