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The Impact of Seasonal Climate on New Case Detection Rate of Leprosy in Brazil (2008–2012)

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The Impact of Seasonal Climate on New Case Detection Rate of Leprosy in Brazil (2008–2012) Lepr Rev (2017) 88, 533–542 The impact of seasonal climate on new case detection rate of leprosy in Brazil (2008–2012) ALINE CRISTINA ARAU´ JO ALCAˆ NTARA ROCHA*, WASHINGTON LEITE JUNGER**, WESLEY JONATAR ALVES DA CRUZ* & ELIANE IGNOTTI* *University of the State of Mato Grosso - UNEMAT, Rua dos Tuiuiu´s, 660 Vila Mariana, Ca´ceres-MT-Brasil, CEP. 78200-000 **University of the State of Rio de Janeiro - UERJ, Institute of Social Medicine, Rio de Janeiro - RJ, Brasil Accepted for publication 2 August 2017 Summary Objective: To examine the impact of climatic seasonality in the new case detection rate of leprosy in Brazil according to geographical regions, climates and biomes over a 5-year period, 2008–2012. Methods: We conducted an ecological study of the monthly new case detection rate of leprosy in spatial aggregation of Brazilian geographical regions, climates and biomes, applying a linear regression models with Poisson function to estimate seasonal rates using January as the reference month. Results: Monthly seasonal patterns of leprosy detection rates were recorded between different geographic regions, biomes and climates, with a predominance of increases in the autumn, in the months of March and May, and in winter in the month of August. Conclusions: The detection rate of leprosy in Brazil has a seasonal pattern with specific variations between geographical regions, climates, and biomes. The highest peaks in the detection rates were observed in May (autumn) and in August (winter). In addition to the supply and accessibility of healthcare services, these patterns, may also be related to cultural and environmental factors. Keywords: Detection, Seasons, Environment Introduction Seasonal studies of the incidence of infectious diseases in areas of tropical and subtropical climates are frequent, particularly for dengue, malaria, influenza and measles among others.1–3 Environmental determinants are included among the main factors related to Correspondence to: Aline Cristina Arau´jo Alcaˆntara Rocha, University of the State of Mato Grosso – UNEMAT, Rua dos Tuiuiu´s, 660 Vila Mariana, Ca´ceres-MT-Brasil, CEP. 78200-000 (e-mail: [email protected]) 0305-7518/17/064053+10 $1.00 q Lepra 533 534 A.C.A.A. Rocha et al. seasonality, although the exact mechanism of transmission of these diseases is poorly understood. However, there are rare exceptions.4 Leprosy is a contagious, infectious disease, the transmission factors of which are mainly related to unfavourable living conditions and social inequalities. It has a high detection rate in Brazil, with 15·44 cases per 100,000 inhabitants in 2013. The territorial distribution is heterogeneous, with the most endemic areas being the North, Northeast and Midwest (http://www.who.int/lep/resources/Cluster_analyses/en/). The epidemiological distribution of the disease requires an understanding of many regional aspects. Brazil is a broadly diverse country in its politics, culture, economy and environment. It is organised into five geographical regions, five climates and six biomes.5 It is organised in five geographic regions classified in North, Northeast, Southeast, South and Midwest; and, presents five most important climates defined in Equatorial, Temperate, Central Tropical Brazil, Eastern Tropical Northeast, and Equatorial Tropical Zone. Other environmental and geographical classification refers to biomes. It means ‘a set of life’ (vegetal and animal) constituted by the grouping of contiguous and identifiable types of vegetation on a regional scale, with similar geoclimatic conditions and shared history of changes, resulting in a biological diversity of its own.5–7 The six biomes are ‘Amazon’, ‘Cerrado’, ‘Pantanal’, ‘Atlantic Forest’, ‘Pampa’, and ‘Caatinga’.6 This territorial classification (geographical region, climate and biomes) overlapping in some way, and they share similarities; however, there are important distinctions. With regard to geographical and environmental characteristics, the North region includes the Equatorial climate, a small part of the Equatorial Tropical Zone climate in the far north and the Amazon biome; the Northeast region includes the Eastern Tropical Northeast climate, the Equatorial Tropical Zone climate, and part of the Central Tropical Brazil climate, along with the ‘Cerrado’, ‘Caatinga’ and Atlantic Forest biomes; the Southeast Region includes the Central Tropical Brazil climate and ‘Cerrado’ and Atlantic Forest biomes; the South region includes the Central Tropical Brazil and Temperate climates and the ‘Pampa’ and Atlantic Forest biomes, and the Midwest region includes the Equatorial and Central Tropical Brazil climates along with the Amazon, ‘Pantanal’ and ‘Cerrado’ biomes.5,6 With such a diversity of climates and biomes, we can assume that endemic distribution analysis conducted only by geographical region cannot possibly account for all the many variations found in Brazil (Figure 1). It is recognised and understood that leprosy is not a seasonal disease and that efforts to diagnose and treat this disease should continue year-round. However, the relationship between leprosy and environmental factors has gained strength in recent years thanks to advancements in molecular biology.8 Thus, an analysis of leprosy detection as it pertains to the seasons may offer insights into public health resource allocation to better control the disease. This study aimed to examine the impact of climate seasonality on the new case detection rate of leprosy according to Brazilian geographical regions, climates, and biomes in a 5-year period (2008–2012). Methods We conducted an ecological analysis of the impact of climate seasonality on the detection rate of leprosy in Brazil for the 5 years between the beginning of 2008 and the end of 2012. We used the detection rate of new cases of leprosy as a proxy for the leprosy incidence rate. Seasonality of leprosy 535 Figure 1. Brazil - Geographical regions, climate and biomes. Source: IBGE. New cases of leprosy reported per municipality in Brazil during the proposed period were obtained from the Notifiable Diseases Information System (SINAN). Population estimates for calculating rates were obtained from the Brazilian Institute of Geography and Statistics (IBGE). We aggregated the number of new cases of leprosy diagnosed by Brazilian municipalities in monthly totals by geographic region, climate, and biome. For municipalities with more than one biome or climate, we classified them according to the spatial location of the urban centre, where most of the population is concentrated, through the overlap of cartographic databases of IBGE climates and biomes using ArcGIS version 9.2 (ESRI, California, USA). The data were organised in spreadsheets by geographic region, climate, and biome, each containing the monthly aggregate number of new leprosy cases and the annual estimated population in the twelve months for years 2008 to 2012. To identify the climate seasonality in leprosy detection rate we used linear regression models with Poisson function for rates, using January as the reference month. The outcome variable was the number of new leprosy cases per month. The logarithm of the population for each spatial unit of geographical regions, climates, and biomes was included in the model as offset. The analyses were performed using R version 3.1.0 (R Foundation for Statistical 536 A.C.A.A. Rocha et al. Computing, Vienna, Austria) at 5% significance level. The regression coefficients estimates obtained from modelling were converted into monthly Relative Risks and calculated as monthly percentage variations in leprosy detection rates. For comparative analysis of the spatial distribution of the variation in the seasonal leprosy detection rate, we considered only the statistically significant results when preparing maps by geographic regions, climates, and biomes, using ArcGIS 9.2. To facilitate the presentation of maps, we selected the first month of every season of the year, that is, March for autumn, June for winter, September for spring, and December for summer. This study was conducted using secondary data from the Ministry of Health (MoH) and the IBGE. Since the data is in the public domain, we have received an official statement dismissing the mandatory submission to the research ethics committee. Results As shown in Table 1, the detection rate of leprosy in Brazil increased in the March and May (autumn) and August (winter), and decreased in the December (summer). In the analysis of seasonality by geographic regions, monthly seasonal patterns were similar in the North, Northeast, Southeast, and Midwest regions, which showed statistically significant variations in leprosy detection rates for almost every month of the year. The largest increases were observed in March and May (autumn) and August (winter) when compared to January as a reference and the largest decreases were observed in December (summer). The seasonal pattern for the South region was distinct from the other regions, with the largest increases in the October and November (spring), March to May (autumn) and August (winter) (Table 2). The seasonality on detection rate variations in the Equatorial and Tropical climates was similar in the North and South regions. Nevertheless, for the Semi-arid, Highland Tropical, and Subtropical climates, distinct variations were observed in the geographic regions where they are found (Figure 2). Table 1. Seasonality analysis of the detection rate of leprosy according to the months of the year * in Brazil, 2008– 2012 Months b1 % variation CI (95%) P value
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