Mortality from neglected tropical diseases in the state of Maranhão, Brazil: a guidance for health planning in vulnerable areas

Mortalidade por doenças tropicais negligenciadas no estado do Maranhão, Brasil: um guia para o planejamento de saúde em áreas vulneráveis

Abstract

Neglected tropical diseases (NTD) are chronic infectious diseases affecting low-income populations (mainly in tropical and subtropical climates), characterized by high morbidity and low mortality. This study described the epidemiology of mortality from NTDs in the state of Maranhão, Brazil. Data from the Brazilian Mortality Information System evidenced 2,642 deaths from NTDs between 2001 and 2021; 31.13% were related to leishmaniasis (mainly the visceral form) and 20.82% to leprosy. A total of 211 municipalities in Maranhão had registered mortality due to NTDs. We identified, high-risk spatial and spatiotemporal conglomerates in the western and southern areas of Maranhão, comprising mostly municipalities with high social vulnerability and low human development. Integrated mapping of NTDs may allow the development of public intervention policies and is an important strategy to control and eliminate NTDs in the most affected populations.

Keywords:
neglected disease; epidemiology; tropical climate

Resumo

As doenças tropicais negligenciadas (DTN) são doenças infecciosas crônicas que afetam populações de baixa renda (principalmente em climas tropicais e subtropicais), causando morbidade e mortalidade. Este estudo descreveu a epidemiologia da mortalidade por DTNs no estado do Maranhão, Brasil. Dados do Sistema de Informação sobre Mortalidade do Brasil evidenciaram 2.642 mortes por DTNs entre 2001 e 2021; 31,13% estavam relacionadas à leishmaniose (principalmente a forma visceral) e 20,82% à hanseníase. Um total de 211 municípios no Maranhão apresentaram mortes por DTNs, com conglomerados espaciais e espaço-temporais de alto risco identificados nas áreas oeste e sul, compreendendo principalmente municípios com alta vulnerabilidade social e baixo desenvolvimento humano. O mapeamento integrado de DTN pode permitir o desenvolvimento de políticas de intervenção pública e é uma estratégia importante para controlar e eliminar DTN nas populações mais afetadas.

Palavras-chave:
doenças negligenciadas; epidemiologia; clima tropical

1. Introduction

Neglected tropical diseases (NTD) are prevalent chronic infectious diseases in tropical and subtropical climates, mainly affecting marginalized and low-income populations in low and middle income countries. The population most affected is found in areas with favorable conditions for the reproduction and spread of vectors (parasites, worms or viruses transmitted by mosquitoes, ticks, sand flies) due to the tropical climate (Hotez et al., 2020; Behrend et al., 2020). However, there is very little interest in developing cures, treatments and research into vaccines to effectively control these diseases (Booth, 2018; Shirley et al., 2022). NTDs are associated with socioeconomic inequality, partly due to insufficient access to basic sanitation, potable water, and adequate habitation (Tidman et al., 2021). Insufficient investments in research and social policies perpetuate the mortality from NTD among low-income populations (Ferreira et al., 2022).

Poverty affects around 40% of the population from Latin America and the Caribbean, having the highest income inequality worldwide (Hotez, 2008). However, NTDs in these regions are also perpetuated by other social determinants of health, such as ethnicity, age, and sex (Fontecha et al., 2021). Brazil has high income inequality, associated with high incidence of morbidity and mortality from NTDs (Ferreira et al., 2023). Additionally, in Brazil, the combined age-standardized rate of disability-adjusted life years (DALY) of 12 NTDs was 232 per 100,000 inhabitants in 2016, corresponding to 0.8% of all causes of DALY in the country (Martins-Melo et al., 2018).

The co-occurence of NTDs in Brazil (especially in the northeast region) requires healthcare services to integrate their mapping capacity and distribution. Spatiotemporal epidemiological analyses can estimate the relationship between indicators of NTD occurrence and environmental or socioeconomic variables, generally modeled as covariates (Hamm et al., 2015). An example of this are the arboviruses (dengue, zika and chikungunya), where the occurrence of epidemic waves of great magnitude and rapid dissemination together with the simultaneous circulation of different arboviruses challenge their timely surveillance (Skalinski et al., 2022). These models provide information on the factors influencing the spatial distribution of the disease and provide spatiotemporal predictions from empirical relationships between the disease and the environment. Thus, understanding the spatial distribution of NTDs may help healthcare services in decision-making (Martins-Melo et al., 2016a).

To date, data exploring the spatial epidemiology of deaths from NTDs in the Brazilian state of Maranhão are scarce (Martins-Melo et al., 2016b). We performed a spatiotemporal analysis of deaths from NTDs registered between 2001 and 2021 to determine priority conglomerate areas. Our findings can improve the development of strategies to control and eliminate NTDs in Maranhão.

2. Methods

2.1. Study area

Maranhão is a state in the northeast of Brazil, between parallels 1°01’ and 10°21’ south and meridians 41°48’ and 48°50’ west. It has a territorial area of 329,651.496 km², 6,775,152 inhabitants, and a population density of 20.55 inhabitants/km², with the largest concentration in the northern mesoregion (2,840,284 inhabitants) in 2022. Also, this state borders to the west by the state of Pará, east by Piauí, and south and southeast by Tocantins (Figure 1). Maranhão has significant social inequalities, with a general social vulnerability index of 0.359 and a human development index of 0.676 in 2021 (IBGE, 2011).

Figure 1
Geographical location of Maranhão.

2.2. Data source

An ecological study was performed with a spatiotemporal analysis of deaths from NTDs in Maranhão between 2001 and 2021. Secondary data were collected from the Mortality Information System of the Brazilian Ministry of Health. All NTDs officially listed by the World Health Organization were included (WHO, 2021), considering the Tenth Revision of the International Statistical Classification of Diseases and Related Health Problems (ICD-10):

1. Diseases caused by protozoa - Chagas (B57), leishmaniasis (visceral and tegumentary [B55]), and human African trypanosomiasis (B56);

2. Diseases caused by helminths - schistosomiasis (B65, N22), ascariasis (B77), hookworm (B76), trichuriasis (B79), onchocerciasis (B73), cysticercosis and teniasis (B68-B69), cutaneous larva migrans (B83), echinococcosis (B67), lymphatic filariasis (B74), dracunculiasis (B72), and other helminthiases (opisthorchiasis [B66. 0], clonorchiasis [B66.1], fascioliasis [B66.3], and paragonimiasis [B66.4]);

3. Diseases caused by bacteria - leprosy (A30, B92), trachoma (A71, B94), Buruli ulcer (A31.1), and endemic treponematoses (yaws [A66], pinta [karate; A67], and syphilis [A65]);

4. Diseases caused by viruses - rabies (A82), dengue (A90-A91), and chikungunya (A92);

5. Diseases caused by fungi - mycetoma (B47), chromoblastomycosis (B43), histoplasmosis (B39), coccidioidomycosis (B38), paracoccidioidomycosis (B41), sporotrichosis (B42), and cryptococcosis (B45);

6. Diseases caused by ectoparasites - scabies (B86), tungiasis (B88.1), cutaneous larva migrans (B83), pediculosis (B85), and myiasis (B87);

7. Accidents with venomous animals - snakebite poisoning (T63.0) and contact with venomous serpents or lizards (X20).

Data from the population census of 2010 and annual intercensal estimates (2001 to 2009 and 2011 to 2021) were obtained in the electronic platform of the Brazilian Institute of Geography and Statistics (IBGE, 2023). In addition, the municipal human development index (composed of health, education, and income dimensions) was obtained using the Brazilian Atlas of Human Development. The social vulnerability index, which comprises a set of indicators for social vulnerabilities (human capital, income and work, and infrastructure), was obtained using the Institute for Applied Economic Research (IPEA, 2023).

2.3. Data analysis

We collected absolute and relative frequencies of deaths and sociodemographic variables, such as sex (male and female), age group (0 to 4 years, 5 to 9 years, 10 to 14 years, 15 to 19 years, 20 to 29 years, 30 to 39 years, 40 to 59 years, and ≥ 60 years), race (white, black, yellow, mixed race, and indigenous), and years of education (illiterate, 1 to 3 years, 4 to 7 years, 8 to 11 years, and ≥ 12 years).

We calculated the crude coefficient of mortality to assess the risk of death from any NTDs (per 100,000 inhabitants) by dividing the number of deaths by the annual mean population (per 100,000 inhabitants) and their respective 95% confidence intervals (95% CI). We determined the difference between the median of deaths of each variable using non-parametric tests. We used Mann-Whitney test for the sex variable, and Kruskal-Wallis test was used for the variables age, ethnicity or race, and years of education. We applied the Dunn post-hoc for comparison between each variable, and excluded from the tests deaths with unreported sociodemographic characteristics. We performed statistical analyses using the GraphPad Prism software version 8.0.0 (San Diego, California, USA).

We calculated the Global Moran's Index and local indicators of spatial association (LISA) to assess global and local spatial autocorrelation, respectively. LISA classifies spatial units based on the presence of positive spatial association, in which the point of association exhibits similar values to the neighborhood (high-high and low-low), or a negative association, in which the point of association has different values to the neighborhood (high-low and low-high) (Chen, 2013). We used a Queen contiguity-based spatial weighting matrix of first-order neighbor type. LISA was spatially represented by considering statistically significant municipalities (p < 0.05), and the pseudo-significance test was performed using the 999 Monte Carlo permutations.

A bivariate analysis assessed the spatial correlation between the coefficient of mortality from NTD and municipal human development and social vulnerability indexes to describe spatial dependence (positive or negative) between them. We calculated the smoothed rate of mortality from NTD (per 100,000 inhabitants) using the local empirical Bayesian method to minimize random variations with small populations and rare events. We excluded two deaths from NTD due to lack of information on the place of residence.

We used Kulldorff's space-time scan statistic to characterize high-risk clusters in time and space through the Poisson discrete probability distribution and following the criteria: circular clusters, with a maximum size of 20% of the population at risk, a maximum temporal cluster size of 50%, no geographical overlap, a minimum aggregation time of two years, and 999 permutations. We classified the cluster high-risk when the relative risk (RR) was > 1. We defined the primary and secondary clusters using a likelihood ratio test (Tango et al., 2011).

We used GeoDa version 1.14 (Center for Geospatial Analysis and Computation, Arizona, USA) for spatial autocorrelation and SaTScan version 9.1.1 software (Department of Medicine of Harvard Medical School, Boston, USA) for scan statistics, and QGIS software version 3.22 (Open Source Geospatial Foundation project) to finalize the thematic maps.

2.4. Ethical aspects

We obtained de-identified NTD mortality data from a secondary database of public domain, not requiring ethical approval and according to resolution 510 of the National Health Council (Guerriero and Minayo, 2019).

3. Results

A total of 2,642 deaths from NTD were recorded between January 2001 and December 2021 in Maranhão, mostly caused by leishmaniasis (n = 981; 37.13%), followed by leprosy (n = 550; 20.82%), accidents with venomous animals (n = 229; 8.67%), and dengue (n = 220; 8.33%; Figure 2A). The highest number of municipalities with deaths from NTD (n = 82) occurred in 2015, and 2016 had the highest coefficient of mortality (2.84 per 100,000 inhabitants; Figure 2B).

Figure 2
Number of deaths from neglected tropical diseases in Maranhão, 2001 - 2021. (A) Deaths by cause; (B) Deaths by number of municipalities and coefficient of mortality. DCP = diseases caused by protozoa; DCH = diseases caused by helminths; DCB = diseases caused by bacteria; DCV = diseases caused by viruses; DCF = diseases caused by fungi; Ecto. = ectoparasites. Source: Mortality Information System (Brasil, 2022).

Most deaths from NTD (n = 1,713; 64.86%; p < 0.0001) and the highest coefficient of mortality (23.87; 95% CI: 21.85 to 25.89) occurred in males. Also, individuals who self-declared brown were the most affected (n = 1,711; 68.19%; p < 0.0001) and had the highest coefficient of mortality (24.57; 95% CI: 22.34 to 26.81). Regarding years of education, illiterate people presented the highest frequency of deaths (n = 744; 37.86%; p < 0.001) and coefficient of mortality (11.97; 95% CI: 10.44 to 13.50), with no significant difference (p = 0.20) compared with one to three years of education. The age group ≥ 60 years had the highest frequency of deaths (n = 832; 31.54%; p < 0.0001) and coefficient of mortality (12.69; 95% CI: 21.85 to 25.89), with no significant difference (p = 0.11) compared with the age group between 40 and 59 years (Figures 3A and 3B).

Figure 3
Sociodemographic characteristics of neglected tropical diseases in Maranhão, 2001 - 2021. (A) Mean coefficient of mortality with 95% confidence interval; (B) Distribution of the number of deaths and difference between the median of each group (Dunn post-hoc). *p < 0.05; **p < 0.001; ***p < 0.0001; NS = not significant.

From 2001 to 2021, 97.23% (n = 211/217) of the municipalities in Maranhão recorded at least one death related to NTD. The distribution of the coefficient of mortality indicated the highest number of deaths in municipalities of western and southern Maranhão. After smoothing, the dispersion reduced and stability increased, with rates ranging from 17.1 to 84.90 per 100,000 inhabitants. The Global Moran’s Index showed positive spatial autocorrelation. Scan analysis identified three spatiotemporal clusters with high risk for mortality from NTD (Figure 4).

Figure 4
Spatial distribution of deaths from neglected tropical diseases (NTD) according to place of residence in Maranhão, Brazil. (A) crude and (B) smoothed coefficient of mortality for NTD; (C) Clustering maps of univariate local indicators of spatial association of the smoothed Bayesian mortality rate for NTD; (D) Spatiotemporal clusters of deaths from NTD.

Figure 5 shows the bivariate analysis of the coefficient of mortality compared with the distribution of social vulnerability and human development (with respective domains). Global Moran's index revealed a positive spatial autocorrelation in the socially vulnerable municipalities, especially in the income and work and human capital domains. The southern Maranhão presented a predominance of clusters of municipalities with a high human development index, primarily related to income and work and longevity.

Figure 5
Clustering maps of bivariate local indicators of spatial association of the smoothed Bayesian mortality rate (per 100,000 inhabitants) and municipal human development and social vulnerability indexes in Maranhão, Brazil.

The primary cluster was detected from 2012 to 2021, including 65 municipalities located mainly in the south and center of Maranhão (RR = 1.87; p < 0.005), with a coefficient of mortality of 3.5 deaths per 100,000 inhabitants. One secondary cluster was identified in the eastern area from 2001 to 2009, comprising six municipalities and a coefficient of mortality of 3.6 deaths per 100,000 inhabitants (RR = 1.82; p < 0.005). Another secondary cluster was in the north from 2008 to 2017, covering ten municipalities with a coefficient of mortality of 17.9 deaths per 100,000 inhabitants (RR = 1.86; p < 0.005) (Table 1).

Table 1
Spatiotemporal clusters of mortality rates from neglected tropical diseases in Maranhão, 2001-2021.

Clusters	Period	Number of municipalities	Radius (km)	Number of deaths	Expected number of deaths	Annual mortality rate a	RR	LLR	p-value
1	2012 to 2021	65	239.95	402	231.43	3.5	1.87	57.59	< 0.0001
2	2001 to 2009	6	71.01	151	85.25	3.6	1.82	21.43	< 0.0001
3	2008 to 2017	10	51.99	80	43.63	3.7	2.39	12.39	< 0.0001

• ^a
  Mortality rates related to neglected tropical diseases (per 100,000 inhabitants) during the time of clustering. RR = relative risk for the cluster compared with the remaining Maranhão; LLR = log likelihood ratio.

4. Discussion

NTDs were responsible for 2,642 deaths in Maranhão during the assessed period, evidencing leishmaniasis as the main cause, followed by leprosy, accidents with venomous animals, and dengue. The present study explored the spatial and spatiotemporal characteristics of NTDs and detected a heterogeneous distribution and high-risk areas in Maranhão. Also, the coefficient of mortality for NTDs increased from 1.11 to 1.69 per 100,000 inhabitants from 2001 to 2021. Correlations between NTDs with municipal social vulnerability and human development indicators revealed high relative risk in vulnerable areas with low human development. Although these diseases are related to poverty and responsible for significant local burden of disease, they do not represent global priorities individually (Engels and Zhou, 2020).

In Piauí (neighboring state of Maranhão), the main causes of death from NTDs from 2001 to 2018 were Chagas disease (55.2%), leishmaniasis (15.7%), and leprosy (13.8%) (Brito et al., 2022). Brazilian estimates revealed that Chagas disease was the leading cause of DALY rates per 100,000 inhabitants among all NTDs in 2016 (70.69; 95% CI: 64.49 to 77.81), followed by schistosomiasis (46.92; 95% CI: 27.54 to 80.71), and dengue (44.87; 95% CI: 30.85 to 63.10). Also, Maranhão obtained a DALY rate of 299.84 (95% CI: 181.50 to 481.34) for NTD in the same year (Martins-Melo et al., 2018).

Leishmaniasis was responsible for 37.13% of the deaths registered in Maranhão between 2001 and 2021. The high risk of death from leishmaniasis (especially the visceral form) in Maranhão was consistent with the expansion of areas with high disease endemicity occurring since 1982 when the first case was diagnosed in São Luís (capital of Maranhão) (Silva et al., 1997). Since then, visceral leishmaniasis has been registered in all mesoregions of the state (Coutinho et al., 2000), with a tendency of increasing until 2023 (Pimentel et al., 2024). The cutaneous leishmaniasis, in general, presents high morbidity and low mortality, as the infection is not normally fatal for the host (Oliveira et al., 2024).

The highest rate of years of life lost (YLL) due to premature death from visceral leishmaniasis in Brazil has been observed among children under one year old, which increased by 131.2% between 1990 and 2000 and 25.7% between 2000 and 2016 (Bezerra et al., 2018). In contrast, years of life lost due to disability (YLD) decreased during the same period for all age groups in the country (Maia-Elkhoury et al., 2019), indicating that the highest mortality for children under one year old occurs in the visceral condition. A prospective cohort study on the factors associated with death from visceral leishmaniasis in Brazil revealed that although patients under five years old were diagnosed earlier, they had a reduced survival rate (Maia-Elkhoury et al., 2019). These findings suggested that the lethality pattern in patients under five years old was related to the severity of the disease.

Leprosy, the second leading cause of death in Maranhão, was identified in 20.82% of deaths in the present study. It was associated with interstate migration with Pará, Tocantins, and Piauí, poor living conditions, and social inequality (Alencar et al., 2012; Murto et al., 2013). Also, leprosy corresponded to 7,732 of 12,491,280 deaths (0.1%) registered in Brazil between 2000 and 2011, with an annual mean age-adjusted mortality rate of 0.43 deaths per 100,000 inhabitants (95% CI: 0.40 to 0.46). In addition, the burden of deaths in this study was increased in men, older adults, black, and leprosy-endemic regions (Martins-Melo et al., 2016). A study conducted in 16 municipalities in the southwest of Maranhão using Poisson regression models revealed the following risk factors associated with multibacillary leprosy: individuals over 15 years old; male; with less than eight years of education; with grade I, II, or “not assessed” disability; and with type 1, 2, or both reactional condition (Silva et al., 2023). Thus, a combined approach of NTD may help healthcare services to strengthen control measures (Ribeiro et al., 2018).

Accidents with venomous animals (8.67%) and dengue (8.33%) were the third and fourth leading causes of death from NTD in Maranhão, respectively. In the state of Ceará (northeastern Brazil), the highest rate of accidents with venomous animals between 2007 and 2019 was related to scorpion stings (67.2%), women (52.4%), people aged from 10 to 19 and 40 to 59 years (21.4%), urban areas, and rainy months (Braga et al., 2021). Ophidian accidents and bee and spider stings were also important causes of death due to accidents with venomous animals in Ceará (Braga et al., 2021). In Maranhão, 17,658 cases of accidents with venomous animals were registered between January 2009 and December 2019, mainly in the municipalities of Buriticupu, Arame, and Grajaú and among males aged between 20 and 39 years. Most of the bites occurred from snakes of the genus Bothrops and Crotalus in the western and central mesoregions of Maranhão, areas with a notable expansion of agriculture (Araújo et al., 2023).

Techniques of spatial analysis for NTD in the northeast of Brazil were used in several studies, including visceral leishmaniasis (Machado et al., 2020), leprosy (Souza et al., 2019), dengue (Carmo et al., 2020), Chikungunya and Zika (Costa et al., 2021), and soil-transmitted helminth infections (e.g., ascariasis, trichuriasis, hookworm) (Martins-Melo et al., 2017). They evidenced that NTD frequently occur in this region with significant morbidity and mortality. Also, the spatiotemporal analysis showed a large cluster in the south and center of Maranhão, where agricultural areas are rapidly expanding with advanced deforestation and wildfires. This expansion may lead to significant socio-environmental impacts and reinforce the vulnerability of neglected populations to infectious and parasitic diseases and their persistence in this conglomerate over time. The high burden of NTD may impair current and future generations to meet basic human needs in the long term and hinder neglected populations from achieving sustainable development (Ehrenberg and Ault, 2005), which the COVID-19 pandemic may have exacerbated (Toor et al., 2021).

Deaths from NTD in Maranhão occurred mostly in older adults and males, corroborating results from Sergipe, Piauí, and Argentina (Brito et al., 2022; Costa de Albuquerque et al., 2017; Macías and Hernández, 2019). Men are less likely to seek early care and have work activities with a high risk for exposition to NTD, which may explain their increased mortality (Martins-Melo et al., 2016a; Soares et al., 2014). In addition, deaths in older adults may be explained by the presence of chronic diseases that increase the manifestation of severe forms and hospital stays, enhancing the risk for unfavorable outcomes (Costa de Albuquerque et al., 2017; Hotez, 2019).

Although the present study identified the main causes of death from NTDs and high-risk spatiotemporal clusters in Maranhão, it had limitations due to the ecological design. Also, secondary databases may have underreporting, diagnosis or entrance bias, or imprecision in death certificates (Cerbino-Neto et al., 2009). The lack of information in forms of death investigation hinders the description of variables in epidemiological studies, especially those associated with death outcomes. Thus, information related to the epidemiological and clinical profile of these patients must be fully described (Lima et al., 2019).

This study provided an understanding of the spatiotemporal patterns of NTDs in Maranhão, mainly in the southern and central regions (main clusters). These results may help develop and improve strategies for prevention and control of NTDs by considering local and regional characteristics, especially focusing on municipalities of the primary cluster. Several municipalities were connected in a cluster, indicating a spatiotemporal relationship and possibly influencing the persistence of diseases over generations. In this sense, inter-municipal health managers should collaborate to implement joint actions of health education and improve timely user access to healthcare services at all levels, especially in primary care.

Acknowledgements

Karen Brayner Andrade Pimentel expresses her gratitude to the Fundação de Amparo à Pesquisa e ao Desenvolvimento Científico e Tecnológico do Maranhão (FAPEMA) for the PhD degree scholarship. Francisco Eduardo Almeida de Souza expresses her gratitude to the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior – Brasil (CAPES).

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Publication Dates

• Publication in this collection
  22 Nov 2024
• Date of issue
  2024

History

• Received
  19 May 2024
• Accepted
  30 Sept 2024