Spatiotemporal patterns and integrated approach to prioritize areas for surveillance and control of visceral leishmaniasis in a large metropolitan area in Brazil

Spatiotemporal relationship between agriculture, livestock, deforestation, and visceral leishmaniasis in Brazilian legal Amazon

Visceral leishmaniasis (VL) is an urgent public health concern in Brazil. We evaluated the spatiotemporal distribution of VL to better understand the effects of economic activities related to agriculture, livestock, and deforestation on its incidence in the Brazilian Legal Amazon (BLA). The data on newly confirmed cases of VL in Brazilian municipalities from 2007 to 2020 were extracted from the Brazilian Notifiable Diseases Information System (SINAN) and analyzed. The data on agricultural production (planted area in hectares) and livestock (total number of cattle) were obtained from the Brazilian Institute of Geography and Statistics (IBGE), whereas deforestation data (in hectares) were obtained from the Amazon Deforestation Estimation Project (PRODES). SatScan and the local indicators of spatial association (LISA) were used to identify the spatial and temporal patterns of VL and its relationships with economic and environmental variables. The cumulative incidence rate was found to be 4.5 cases per 100,000 inhabitants. Based on the LISA results, areas with a high incidence of VL and deforestation were identified in the states of Roraima, Pará, and Maranhão. Strengthening deforestation monitoring programs and environmental enforcement actions can help implement public policies to control illegal deforestation and mitigate the socio-environmental vulnerability in the BLA. Therefore, areas identified in this study should be prioritized for controlling VL.

Temporal relationship between human and canine visceral leishmaniasis in an urban area in southeastern Brazil: An application of the ARIMAX model

Visceral leishmaniasis (VL) is a neglected disease of public and animal health importance. With the urbanization of the disease, there is evidence of a temporal correlation between the occurrence of human (HVL) and canine (CVL) visceral leishmaniasis, usually with cases in dogs preceding those in humans. In this context, the objective of this study was to develop a time series model suitable for canine-human transmission of Leishmania infantum. Monthly cases of HVL and CVL from 2006 to 2018 in Belo Horizonte, Minas Gerais, Brazil, were evaluated, and monthly health indicators were calculated for HVL and CVL, i.e., incidence coefficient (HVL_IC) and proportion of seropositive dogs (PSD), respectively. The temporal relationship was evaluated using an autoregressive integrated moving average with exogenous variable (ARIMAX) model for two different periods (January 2006-August 2013 and September 2013-December 2018). During the 13 years studied, 1115 new cases of HVL and 103,358 dogs seropositive for CVL were recorded. HVL_IC and PSD exhibited decreasing trends throughout the first study period (January 2006-August 2013). According to the ARIMAX model adjusted for this period, there was a temporal relationship between HVL_IC and PSD, with HVL_IC being influenced by HVL_IC for the last two and five months and by PSD for the third previous month. For the second study period (September 2013-December 2018), it was not possible to fit an ARIMAX model. This study highlights the improvements made by VL surveillance since 2006 in Belo Horizonte and contributes to a better understanding of the epidemiology of the disease by public health policy-makers, doctors and veterinarians involved in the prevention and control of zoonoses.

Spatio-temporal relative risks and priority areas for visceral leishmaniasis control in Brazil, between 2001 and 2020

Visceral leishmaniasis (VL) is a pressing public health problem in Brazil. The proper implementation of disease control programs in priority areas is a challenge for healthcare managers. The present study aimed to analyze the spatio-temporal distribution and identify high risk areas of VL occurrence in the Brazilian territory. We analyzed data regarding new cases with confirmed diagnosis of VL in Brazilian municipalities, from 2001 to 2020, extracted from the Brazilian Information System for Notifiable Diseases. The Local Index of Spatial Autocorrelation (LISA) was used to identify contiguous areas with high incidence rates in different periods of the temporal series. Clusters of high spatio-temporal risk were identified using the scan statistics. The accumulated incidence rate in the analyzed period was 33.53 cases per 100,000 inhabitants. The number of municipalities that reported cases showed an upward trend from 2001 onward, although there was a decrease in 2019 and 2020. According to LISA, the number of municipalities considered a priority increased in Brazil and in most states. Priority municipalities were predominantly concentrated in the states of Tocantins, Maranhão, Piauí, and Mato Grosso do Sul, in addition to more specific areas of Pará, Ceará, Piauí, Alagoas, Pernambuco, Bahia, São Paulo, Minas Gerais, and Roraima. The spatio-temporal clusters of high-risk areas varied throughout the time series and were relatively higher in the North and Northeast regions. Recent high-risk areas were found in Roraima and municipalities in northeastern states. VL expanded territorially in Brazil in the 21st century. However, there is still a considerable spatial concentration of cases. The areas identified in the present study should be prioritized for disease control actions.

Spatio-temporal and trade export risk analysis of bluetongue disease in France: A case study of China

Bluetongue disease (BT) is a viral disease that can be introduced through imported animals and animal products, affecting local animal husbandry. In this study, the spatial and temporal patterns of BT outbreaks (outbreak: a BT infection in cattle, sheep, or goats on a farm, involving at least one infected animal) in France were analyzed and the risk of introducing bluetongue virus (BTV) into countries through trade was assessed. A spatiotemporal analysis of BT reported during the study period (2015-2018) showed that there were clustered outbreaks of BT in France in 2016 and 2017, with outbreaks concentrated from August to December. The outbreak moved eastward from the center of mainland France to surrounding countries. A semi-quantitative risk analysis framework was established by combining the likelihood assessment and consequence analysis of introducing BTV into trading countries through trade. Exemplified by China, the research showed that in the analysis of the likelihood of BTV from France being introduced into trading countries through live cattle trade, China imports a large number of live cattle, bringing high risks. The likelihood of introducing bovine semen into trading countries was similar to that of live cattle, but the harm caused by the trade in live cattle was higher than that caused by the trade in bovine semen. This risk analysis framework can provide a reference for other countries to quickly assess the risk of bluetongue transmission in import and export trade.