Spatial analysis of reported new cases and local risk of leprosy in hyper-endemic situation in Northeastern Brazil

Inequality of gender, age and disabilities due to leprosy and trends in a hyperendemic metropolis: Evidence from an eleven-year time series study in Central-West Brazil

The present study aimed to investigate the epidemiological situation of leprosy (Hansen’s Disease), in a hyperendemic metropolis in the Central-West region of Brazil. We studied trends over eleven years, both in the detection of the disease and in disabilities, analyzing disparities and/or differences regarding gender and age. This is an ecological time series study conducted in Cuiabá, capital of the state of Mato Grosso. The population consisted of patients diagnosed with leprosy between the years 2008 and 2018. The time series of leprosy cases was used, stratifying it according to gender (male and female), disability grade (G0D, G1D, G2D, and not evaluated) and age. The calendar adjustment technique was applied. For modeling the trends, the Seasonal-Trend decomposition procedure based on Loess (STL) was used. We identified 9.739 diagnosed cases, in which 58.37% were male and 87.55% aged between 15 and 59 years. Regarding detection according to gender, there was a decrease among women and an increase in men. The study shows an increasing trend in disabilities in both genders, which may be related to the delay in diagnosis. There was also an increasing number of cases that were not assessed for disability at the time of diagnosis, which denotes the quality of the services.

In the 2019 report, Brazil had a detection rate of 13.23 per 100.000 inhabitants far from the goal of less than 1 leprosy (Hansen’s Disease) case per 10,000 inhabitants describe by the World Health Organization. The present study aimed to investigate the epidemiological situation of leprosy and its trend between 2008 and 2018 in a hyperendemic metropolis in the Central-West region of Brazil. A total of 9.739 leprosy cases were reported between 2008 and 2018. The majority of cases were male (58.37%), with a predominant age of 15 to 59 years (87.55%). The predominant level of education was incomplete elementary school (43.96%). The disability grade at diagnosis showed that 40.19% had G0D and for the G2D was 8,.06%.There was a predominance in operational classification of multibacillary cases (72.85%). While detection rate trends in females and the majority of the age groups are decreasing, increases are seen in the detection of male patients and patients already suffering from disabilities. Although declining trends were presented, the metropolis is still not close to elimination showing the need prioritize leprosy actions and to improve care for this disease.

The state of the leprosy epidemic in Yunnan, China 2011-2020: A spatial and spatiotemporal analysis, highlighting areas for intervention

BACKGROUND

Despite public health efforts to reduce the leprosy burden in Yunnan, China, leprosy remains an important public health problem in some specific areas. We analyzed the epidemiological characteristics and spatial distribution of leprosy in Yunnan, China, and provide data to guide disease prevention and control efforts.

METHODOLOGY/PRINCIPAL FINDINGS

The surveillance data of newly detected leprosy cases in Yunnan, China, during 2011-2020 were extracted from the LEPROSY MANAGEMANT INFORMATION SYSTEM IN CHINA (LEPMIS), and spatial distribution analysis, spatial autocorrelation analysis, and spatiotemporal scanning were performed with ArcGIS 10.6.1, GeoDa 1.8.8, and SaTScan 9.4.3 software, respectively. A total of 1907 newly detected leprosy cases were reported in Yunnan, China, during 2011-2020. The new case detection rate (NCDR) decreased from 0.62 in 2011 to 0.25 in 2020, with an annual incidence of 0.41/100,000 population. The proportions of multibacillary (MB) cases, cases in female patients, cases causing grade 2 physical disability (G2D), and cases in pediatric patients were 67.07%, 33.93%, 17.99%, and 2.83%, respectively. The number of counties with an incidence above 1/100,000 population decreased from 30 in 2011 to 8 in 2020. The Moran's I of leprosy in Yunnan, China, during 2011-2020 ranged from 0.076 to 0.260, indicating the presence of spatial clusters. Local spatial autocorrelation (LSA) analysis showed that high-high cluster areas (hot spots) were mainly distributed in the southeastern, northern, and northwestern regions. Spatiotemporal scanning showed three clusters with high NCDRs. The probably primary clusters, occurring during January 1, 2011-December 31, 2015, covered 11 counties in the southeastern region (RR = 5.046515, LRR = 271.749664, P = 0.000).

CONCLUSION

The number of leprosy cases in Yunnan decreased overall, although some high-NCDR regions remained. Geographic information system (GIS) analysis coupled with spatial analysis indicated regions with leprosy clusters. Continuous leprosy prevention and control strategies in Yunnan Province should be established, and interventions in high-risk regions should be prioritized and further strengthened.

Measuring endemicity and burden of leprosy across countries and regions: A systematic review and Delphi survey

BACKGROUND

Leprosy is a chronic infectious disease caused by Mycobacterium leprae, the annual new case detection in 2019 was 202,189 globally. Measuring endemicity levels and burden in leprosy lacks a uniform approach. As a result, the assessment of leprosy endemicity or burden are not comparable over time and across countries and regions. This can make program planning and evaluation difficult. This study aims to identify relevant metrics and methods for measuring and classifying leprosy endemicity and burden at (sub)national level.

METHODS

We used a mixed-method approach combining findings from a systematic literature review and a Delphi survey. The literature search was conducted in seven databases, searching for endemicity, burden and leprosy. We reviewed the available evidence on the usage of indicators, classification levels, and scoring methods to measure and classify endemicity and burden. A two round Delphi survey was conducted to ask experts to rank and weigh indicators, classification levels, and scoring methods.

RESULTS

The literature review showed variation of indicators, levels, and cut-off values to measure leprosy endemicity and/or burden. The most used indicators for endemicity include new case detection rate (NCDR), new cases among children and new cases with grade 2 disability. For burden these include NCDR, MB cases, and prevalence. The classification levels 'high' and 'low' were most important. It was considered most relevant to use separate scoring methods for endemicity and burden. The scores would be derived by use of multiple indicators.

CONCLUSION

There is great variation in the existing method for measuring endemicity and burden across countries and regions. Our findings contribute to establishing a standardized uniform approach to measure and classify leprosy endemicity and burden at (sub)national level, which would allow effective communication and planning of intervention strategies.

Leprosy in the context of the Family Health Strategy in an endemic scenario in Maranhão: prevalence and associated factors

This study aimed to describe the prevalence of leprosy and verify the factors associated with multibacillary clinical types in a Family Health Strategy priority setting to control and monitor the disease in northeastern Brazil. This cross-sectional study used data from the Notifiable Diseases Information System related to leprosy cases notified in Imperatriz, Maranhão, between 2008 and 2017. The prevalence was determined yearly and for the period. Poisson regression models with a significance level of 5% were employed to associate the variables and the multibacillary clinical types. Most of the 2,476 leprosy cases analyzed referred to multibacillary clinical types. The prevalence ranged from 7.8 and 15.6/10,000 inhabitants, with high and very high endemicity levels. The variables male, age groups between 30 and 59 years and ≥60 years, schooling <8 years, level 2 physical disability, types 1 and 2 reactive episodes, and urban residence area showed significant associations (p≤0.05) with multibacillary clinical types. Such findings can serve as a basis for elaborating and implementing leprosy control and surveillance measures, gearing actions to the most vulnerable groups, and becoming more effective.

Spatial-temporal analysis of leprosy in a priority Brazilian northeast municipality for disease control

OBJECTIVES

to analyze the spatial-temporal distribution of leprosy in a priority municipality for leprosy control.

METHODS

ecological study, conducted in a city in the Northeast of Brazil, whose analysis units were census sectors. The study used compulsory notification data for cases registered between 2008 and 2017. TerraView software and the Batch Geocode tool was used for geocoding. The detection of spatial-temporal agglomerations of high relative risks was done by scanning statistics.

RESULTS

the spatial-temporal distribution of cases was heterogeneous, creating four agglomerations of high relative risks in the urban area of the municipality between the years 2008 and 2012; and annual prevalence rates classified from high to hyperendemic.

CONCLUSIONS

areas of higher risk and concentration of the disease in space-time were linked to the characteristics of high population density and social vulnerability of these spaces, raising the prioritization of health professionals' actions, systems, and services for control, and monitoring the disease.

Social inequalities and their association with the leprosy burden in a Brazilian city of low endemicity: An ecological study

OBJECTIVE

To analyse the association between social inequalities and the leprosy burden in a low endemicity scenario in the state of São Paulo, Brazil.

METHODS

This ecological study was carried out in the city of Ribeirão Preto, state of São Paulo, Brazil, considering leprosy cases notified from 2006 to 2016. Regarding social inequalities, dimensions related to high household density, literacy, home occupation conditions, health conditions, household income, ethnicity and age were considered. The generalised additive model for location, scale and shape (GAMLSS) was used to verify the association between the social inequalities and leprosy burden.

RESULTS

The increase in men and women with no education and people with an income of 1 to 2 minimum wages was associated with a relative increase in the number of leprosy cases (7.37%, 7.10% and 2.44%, respectively). Regarding the ethnicity variables, the increase in the proportion of men (black) and women (mixed race) with no schooling was associated with a relative increase in the number of cases of the disease (10.77% and 4.02%, respectively). Finally, for people of mixed race or ethnicity, the increase in the proportion of households with 1/2 to 1 minimum wage was related to a relative decrease in the total number of cases (-4.90%).

CONCLUSION

The results show that the determinants associated with the increase in leprosy cases are similar to those in Brazilian hyperendemic regions, and that even in cities with low endemicity, social inequality is one of the main determinants of the disease.

Geospatial epidemiology of leprosy in northwest Bangladesh: a 20-year retrospective observational study

Background

Leprosy is known to be unevenly distributed between and within countries. High risk areas or ‘hotspots’ are potential targets for preventive interventions, but the underlying epidemiologic mechanisms that enable hotspots to emerge, are not yet fully understood. In this study, we identified and characterized leprosy hotspots in Bangladesh, a country with one of the highest leprosy endemicity levels globally.

Methods

We used data from four high-endemic districts in northwest Bangladesh including 20 623 registered cases between January 2000 and April 2019 (among ~ 7 million population). Incidences per union (smallest administrative unit) were calculated using geospatial population density estimates. A geospatial Poisson model was used to detect incidence hotspots over three (overlapping) 10-year timeframes: 2000–2009, 2005–2014 and 2010–2019. Ordinal regression models were used to assess whether patient characteristics were significantly different for cases outside hotspots, as compared to cases within weak (i.e., relative risk (RR) of one to two), medium (i.e., RR of two to three), and strong (i.e., RR higher than three) hotspots.

Results

New case detection rates dropped from 44/100 000 in 2000 to 10/100 000 in 2019. Statistically significant hotspots were identified during all timeframes and were often located at areas with high population densities. The RR for leprosy was up to 12 times higher for inhabitants of hotspots than for people living outside hotspots. Within strong hotspots (1930 cases among less than 1% of the population), significantly more child cases (i.e., below 15 years of age) were detected, indicating recent transmission. Cases in hotspots were not significantly more likely to be detected actively.

Conclusions

Leprosy showed a heterogeneous distribution with clear hotspots in northwest Bangladesh throughout a 20-year period of decreasing incidence. Findings confirm that leprosy hotspots represent areas of higher transmission activity and are not solely the result of active case finding strategies.

Supplementary Information

The online version contains supplementary material available at 10.1186/s40249-021-00817-4.

Spatial analysis of epidemiological and quality indicators of health services for leprosy in hyperendemic areas in Northeastern Brazil

Leprosy is a public health problem due to the physical disabilities and deformities it causes. This study aimed to describe new leprosy cases using an operational classification and analyzing spatial patterns by means of epidemiological and quality indicators of health services in Pernambuco State, Brazil, between 2005 and 2014. This was an ecological study performed in 184 municipalities grouped into 12 health regions units for analysis. To analyze spatial patterns, the Bayesian local empirical method and Moran's spatial autocorrelation indicator were applied and box and Moran maps were used. Individuals aged ≥15 years old, grade zero physical disability and complete remission as the treatment outcome were predominant in both paucibacillary and multibacillary cases, the only difference was the predominance of females (n=9,286; 63.00%) and males (n=8,564; 60.70%), respectively. These variables were correlated (p<0.05) with the operational classification. The overall detection rate showed three high-priority areas; the indicator rate of grade 2 physical disability revealed clusters in regions IV, V, and VI; and the indicator rate of cases with some degree of disability showed precarious municipalities in seven health regions. Pernambuco maintains an active chain of transmission and ongoing endemicity of leprosy. Therefore, spatial analysis methods allow the identification of priority areas for intervention, thereby supporting the disease elimination strategy.

Trends and forecasts of leprosy for a hyperendemic city from Brazil's northeast: Evidence from an eleven-year time-series analysis

This study’s objective was to estimate the temporal trends of leprosy according to sex and age groups, as well as to estimate and predict the progression of the disease in a hyperendemic city located in the northeast of Brazil. This ecological time-series study was conducted in Imperatriz, Maranhão, Brazil. Leprosy cases diagnosed between 2006 and 2016 were included. Detection rates stratified by sex and age groups were estimated. The study of temporal trends was accomplished using the Seasonal-Trend Decomposition method and temporal modeling of detection rates using linear seasonal autoregressive integrated moving average model according to Box and Jenkins method. Trend forecasts were performed for the 2017–2020 period. A total of 3,212 cases of leprosy were identified, the average incidence among men aged between 30 and 59 years old was 201.55/100,000 inhabitants and among women in the same age group was 135.28/100,000 inhabitants. Detection rates in total and by sex presented a downward trend, though rates stratified according to sex and age presented a growing trend among men aged less than 15 years old and among women aged 60 years old or over. The final models selected in the time-series analysis show the forecasts of total detection rates and rates for men and women presented a downward trend for the 2017–2020 period. Even though the forecasts show a downward trend in Imperatriz, the city is unlikely to meet a significant decrease of the disease burden by 2020.

Epidemiology and Spatiotemporal Patterns of Leprosy Detection in the State of Bahia, Brazilian Northeast Region, 2001⁻2014

The detection of leprosy cases is distributed unequally in Brazil, with high-risk clusters mainly in the North and Northeast regions. Knowledge on epidemiology and spatiotemporal patterns of leprosy occurrence and late diagnosis in these areas is critical to improve control measures. We performed a study including all leprosy cases notified in the 417 municipalities of Bahia state, from 2001 to 2014. New case detection (overall and pediatric <15 years) and grade 2 disability (G2D) rates were calculated and stratified according to socio-demographic variables. Spatial analyses were performed to detect high-risk areas for occurrence and late diagnosis. A total of 40,060 new leprosy cases was reported in the period (mean = 2861 cases/year), 3296 (8.2%) in <15-year-olds, and 1921 (4.8%) with G2D. The new case detection rate was 20.41 cases/100,000 inhabitants (95% CI: 19.68–21.17). A higher risk was identified in older age groups (RR = 8.45, 95% CI: 7.08–10.09) and in residents living in the state capital (RR = 5.30, 95% CI: 4.13–6.79), in medium-sized cities (RR = 2.80; 95% CI: 2.50–3.13), and in the west (RR = 6.56, 95% CI: 5.13–8.39) and far south regions of the state (RR = 6.56, 95% CI: 5.13–8.39). A higher risk of G2D was associated with male gender (RR = 2.43, 95% CI: 2.20–2.67), older age (RR = 44.08, 95% CI: 33.21–58.51), Afro-Brazilian ethnicity (RR = 1.59; 95% CI: 1.37–1.85), living in medium-sized cities (RR = 2.60; 95% CI: 2.27–2.96) and residency in the north (RR = 5.02; 95% CI: 3.74–6.73) and far south (RR = 7.46; 95% CI: 5.58–9.98) regions. Heterogeneous space–time patterns of leprosy distribution were identified, indicating high endemicity, recent transmission, and late diagnosis. This heterogeneous distribution of the disease was observed throughout the study period. Leprosy remains a relevant public health problem in Bahia state. The disease has a focal distribution. We reinforce the importance of integrating surveillance, prevention and control actions in regions of higher risk of leprosy detection and late diagnosis, and in the most vulnerable populations.