Estimating underreporting of leprosy in Brazil using a Bayesian approach

Temporal trends and spatial analysis of leprosy surveillance indicators in the municipalities of the state of Mato Grosso, 2008-2022

BACKGROUND

In 2022, Mato Grosso (MT, Brazil) reported the highest detection rate of new leprosy cases (66.20 per 100,000 inhabitants) among all Brazilian states. Monitoring of leprosy indicators is an important control strategy in hyperendemic areas. We aimed to describe the temporal trends and identify clusters of municipalities according to leprosy surveillance indicators in MT between 2008 and 2022.

METHODS

Data from the Notifiable Diseases Information System were used to analyze new case detection rate of leprosy (NCDR), new case detection rate of leprosy among children aged <15 years (NCD15), and rate of new cases with grade 2 physical disability (G2DR). Spatial scan statistics with pure spatial analysis and spatial autocorrelation maps were used to analyze the spatial patterns. Joinpoint regression was used to estimate the annual percentage change (APC) in these indicators.

RESULTS

The NCDR decreased (APC: -20.2%, 95% confidence interval (CI): -38.7% to -7.4%) between 2019 and 2021. The NCD15 also decreased (APC: -19.2%, 95% CI: -36.4% to -10.3%) between 2018 and 2022. Conversely, the G2DR remained stable throughout the study (APC: 3.2%, 95% CI: -0.1% to 6.7%). Global Moran's index (Moran's I) confirmed the existence of spatial dependence among the municipalities for NCDR (Moran's I=0.348), NCD15 (Moran's I=0.269), and G2DR (Moran's I=0.275). Clusters with high NCDR levels included 13 municipalities in the northern and eastern macroregions, while clusters with high G2DR levels included 12 municipalities in the northwestern, northern, and eastern macroregions.

CONCLUSIONS

The NCDR and NCD15 decreased, but the G2DR remained stable between 2018 and 2022. The coronavirus disease 2019 (COVID-19) pandemic had a potential negative impact on leprosy case detection, highlighting the need to strengthen leprosy surveillance efforts. The identified clusters of MT municipalities can significantly assist in this task.

Trend in the epidemiological risk of leprosy in the state of Goiás-Brazil between 2010 and 2021

OBJECTIVE

To analyze trends in epidemiological risk of leprosy in Goiás state, Brazil, and its health macro-regions, between 2010 and 2021.

METHOD

This is a time series analysis of the composite leprosy epidemiological risk index in Goiás. We used cases held on the Notifiable Health Conditions Information System for calculating indicators separately and risk, classified as high, medium, low and very low. Trends were analyzed using Prais-Winsten linear regression and risk maps were produced.

RESULTS

Goiás showed high leprosy endemicity (24.8 cases/100,000 inhabitants) and medium epidemiological risk between 2019 and 2021 (0.58). A stationary trend was found (annual percentage change, 0.50; 95% confidence interval, -3.04; 4.16) for risk of leprosy in Goiás as a whole and in its Central-West and Central-Southeast macro-regions.

CONCLUSION

There is need for actions to reduce the epidemiological risk of leprosy, especially where its trend is stationary, this includes early screening for new cases and health education.

MAIN RESULTS

Leprosy persists in Goiás state, Brazil, in an endemic form, with heterogeneous distribution. There has been a reduction in the number of municipalities with high epidemiological risk of leprosy, but challenges include active transmission and late diagnosis.

IMPLICATIONS FOR SERVICES

Long-term strategies for prevention, early detection, treatment and monitoring of people with leprosy and their contacts are needed.

PERSPECTIVES

It is crucial to strengthen health policies targeting leprosy in Goiás state, prioritizing continuing education and training programs for health professionals working in the entire territory.

Temporal trends and space-time distribution of leprosy relapse in Brazil from 2001 to 2021

BACKGROUND

To analyse the temporal trends and spatiotemporal distribution of leprosy relapse in Brazil from 2001 to 2021.

METHODS

An ecological study with a temporal trend approach and space-time analysis of leprosy relapse in Brazil was carried out with data from the Notifiable Diseases Information System.

RESULTS

A total of 31 334 patients who experienced leprosy relapse were identified. The number of recurrent cases tended to increase throughout the study period, and this increase was significant among females and in almost all age groups, except for those <15, 50-59 and ≥70 y. Several clusters of high- and low-risk patients were identified across all regions with a heterogeneous distribution.

CONCLUSIONS

The burden of relapse showed an increasing trend in some groups and was distributed in all regions.

Evaluating active leprosy case identification methods in six districts of Nepal

BACKGROUND

Nepal has achieved and sustained the elimination of leprosy as a public health problem since 2009, but 17 districts and 3 provinces with 41% (10,907,128) of Nepal's population have yet to eliminate the disease. Pediatric cases and grade-2 disabilities (G2D) indicate recent transmission and late diagnosis, respectively, which necessitate active and early case detection. This operational research was performed to identify approaches best suited for early case detection, determine community-based leprosy epidemiology, and identify hidden leprosy cases early and respond with prompt treatment.

METHODS

Active case detection was undertaken in two Nepali provinces with the greatest burden of leprosy, Madhesh Province (40% national cases) and Lumbini Province (18%) and at-risk prison populations in Madhesh, Lumbini and Bagmati provinces. Case detection was performed by (1) house-to-house visits among vulnerable populations (n = 26,469); (2) contact examination and tracing (n = 7608); in Madhesh and Lumbini Provinces and, (3) screening prison populations (n = 4428) in Madhesh, Lumbini and Bagmati Provinces of Nepal. Per case direct medical and non-medical costs for each approach were calculated.

RESULTS

New case detection rates were highest for contact tracing (250), followed by house-to-house visits (102) and prison screening (45) per 100,000 population screened. However, the cost per case identified was cheapest for house-to-house visits [Nepalese rupee (NPR) 76,500/case], followed by contact tracing (NPR 90,286/case) and prison screening (NPR 298,300/case). House-to-house and contact tracing case paucibacillary/multibacillary (PB:MB) ratios were 59:41 and 68:32; female/male ratios 63:37 and 57:43; pediatric cases 11% in both approaches; and grade-2 disabilities (G2D) 11% and 5%, respectively. Developing leprosy was not significantly different among household and neighbor contacts [odds ratios (OR) = 1.4, 95% confidence interval (CI): 0.24-5.85] and for contacts of MB versus PB cases (OR = 0.7, 95% CI 0.26-2.0). Attack rates were not significantly different among household contacts of MB cases (0.32%, 95% CI 0.07-0.94%) and PB cases (0.13%, 95% CI 0.03-0.73) (χ2 = 0.07, df = 1, P = 0.9) and neighbor contacts of MB cases (0.23%, 0.1-0.46) and PB cases (0.48%, 0.19-0.98) (χ2 = 0.8, df = 1, P = 0.7). BCG vaccination with scar presence had a significant protective effect against leprosy (OR = 0.42, 0.22-0.81).

CONCLUSIONS

The most effective case identification approach here is contact tracing, followed by house-to-house visits in vulnerable populations and screening in prisons, although house-to-house visits are cheaper. The findings suggest that hidden cases, recent transmission, and late diagnosis in the community exist and highlight the importance of early case detection.

Leprosy prevalence spatial distribution and trend in a health region in Northeast Brazil, 2008-2017: an ecological study

MAIN RESULTS

A total of 4,029 leprosy cases were notified. Mean prevalence varied between 2.0 and 11.5 cases/10,000 inhab. Spatial distribution of the cases was heterogeneous and there was a falling prevalence trend over the years studied.

IMPLICATIONS FOR SERVICES

These findings point to the need to strengthen active tracing strategies and expand health actions and services targeting leprosy, with the aim of increasing detection and early treatment of cases.

PERSPECTIVES

It is important to carry out epidemiological investigations on the spatial distribution and prevalence of leprosy in other health regions in the state, in order to identify other areas with greater vulnerability to leprosy.

OBJECTIVE

to analyse the spatial distribution and trend of leprosy in municipalities of a health region in a Northeast Brazilian state.

METHODS

this was an ecological time-series study based on compulsory notification of leprosy cases by the municipalities covered by the Imperatriz-MA Regional Health Management Unit, between 2008 and 2017; prevalence and mean prevalence for the period were calculated; spatial analysis of the area was carried out and maps were generated using ArcGis 10.5. Prais-Winsten regression was used for trend analysis.

RESULT

4,029 cases of the disease were identified, and average prevalence ranged from 2.0 to 11.5 cases/10,000 inhabitants-year. The overall trend was downward. Governador Edson Lobão had the highest prevalence, 11.5 cases/10,000 inhabitants, and Lajeado Novo had the lowest prevalence, 2.0 cases/10,000 inhabitants.

CONCLUSION

spatial distribution of leprosy cases was heterogeneous in the municipalities studied and prevalence had a falling trend.

Estimating the real burden of gestational syphilis in Brazil, 2007-2018: a Bayesian modeling study

Background

Although several studies have estimated gestational syphilis (GS) incidence in several countries, underreporting correction is rarely considered. This study aimed to estimate the level of under-registration and correct the GS incidence rates in the 557 Brazilian microregions.

Methods

Brazilian GS notifications between 2007 and 2018 were obtained from the SINAN-Syphilis system. A cluster analysis was performed to group microregions according to the quality of GS notification. A Bayesian hierarchical Poisson regression model was applied to estimate the reporting probabilities among the clusters and to correct the associated incidence rates.

Findings

We estimate that 45,196 (90%-HPD: 13,299; 79,310) GS cases were underreported in Brazil from 2007 to 2018, representing a coverage of 87.12% (90%-HPD: 79.40%; 95.83%) of registered cases, where HPD stands for the Bayesian highest posterior density credible interval. Underreporting levels differ across the country, with microregions in North and Northeast regions presenting the highest percentage of missed cases. After underreporting correction, Brazil's estimated GS incidence rate increased from 8.74 to 10.02 per 1000 live births in the same period.

Interpretation

Our findings highlight disparities in the registration level and incidence rate of GS in Brazil, reflecting regional heterogeneity in the quality of syphilis surveillance, access to prenatal care, and childbirth assistance services. This study provides robust evidence to enhance national surveillance systems, guide specific policies for GS detection disease control, and potentially mitigate the harmful consequences of mother-to-child transmission. The methodology might be applied in other regions to correct disease underreporting.

Funding

National Council for Scientific and Technological Development; The Bill Melinda Gates Foundation and Wellcome Trust.

Effectiveness of population-wide screening and mass drug administration for leprosy control in Kiribati: the COMBINE protocol

INTRODUCTION

Progress towards leprosy elimination is threatened by increasing incidence in 'hot-spot' areas where more effective control strategies are urgently required. In these areas, active case finding and leprosy prevention limited to known contacts is insufficient for control. Population-wide active case-finding together with universal prevention through mass drug administration (MDA) has been shown to be effective in 'hot-spot' areas, but is logistically challenging and expensive. Combining leprosy screening and MDA with other population-wide screening activities such as for tuberculosis may increase programme efficiency. There has been limited evaluation of the feasibility and effectiveness of combined screening and MDA interventions. The COMBINE study aims to bridge this knowledge gap.

METHODS AND ANALYSIS

This implementation study will assess the feasibility and effectiveness of active leprosy case-finding and treatment, combined with MDA using either single-dose rifampicin or rifamycin-containing tuberculosis preventive or curative treatment, for reducing leprosy incidence in Kiribati. The leprosy programme will run over 2022-2025 in concert with population-wide tuberculosis screening-and-treatment in South Tarawa. The primary research question is to what extent the intervention reduces the annual leprosy new case detection rate (NCDR) in adults and children compared with routine screening and postexposure prophylaxis (PEP) among close contacts (baseline leprosy control activities). Comparisons will be made with (1) the preintervention NCDR separably among adults and children in South Tarawa (before-after study) and (2) the corresponding NCDRs in the rest of the country. Additionally, the postintervention prevalence of leprosy obtained from a survey of a 'hot-spot' sub-population will be compared with prevalence documented during the intervention. The intervention will be implemented in collaboration with the Kiribati National Leprosy Programme.

ETHICS AND DISSEMINATION

Approval has been obtained from the Kiribati Ministry of Health and Medical Services (MHMS), the University of Otago (H22/111) and the University of Sydney (2021/127) Human Research Ethics Committees. Findings will be shared with the MHMS, local communities and internationally through publication.

Spatial analysis of the epidemiological risk of leprosy in the municipalities of Minas Gerais

BACKGROUND

Leprosy remains a significant public health problem of high importance. This investigation aims to analyze the spatial distribution of the leprosy epidemiological risk in the municipalities of Minas Gerais.

METHODS

This ecological study was conducted with new leprosy cases diagnosed from 2004 to 2019 in the municipalities of the state of Minas Gerais. Based on the epidemiological indicators, a composite indicator called the leprosy epidemiological risk index was estimated, classifying municipalities as high, medium, low and very low risk. For the spatial analysis, the global and local spatial autocorrelation statistics were used to identify the spatial distribution of the leprosy epidemiological risk in the periods 2004-2011 and 2012-2019 and classified as High/High, Low/Low, High/Low and Low /High.

RESULTS

Although leprosy is declining in the state of Minas Gerais, the Global Moran Index confirmed the spatial dependence between municipalities for the two analyzed periods, characterizing the formation of clusters. When performing the local spatial autocorrelation, it was found that the macroregions with the highest number of municipalities with high indices, surrounded by other municipalities with high indices (high-high), were Northwest, East, South East, North, and Northeast. The low risk macroregions were Southeast, Center, South-Center and South.

CONCLUSION

Leprosy has a heterogeneous spatial pattern and remains concentrated in historically endemic areas of the state. It underscores the importance of intensifying actions to combat leprosy in these municipalities and macroregions. Promote improved access to health services and combat stigma and prejudice to eliminate leprosy as a public health problem.

Establishing a standard method for analysing case detection delay in leprosy using a Bayesian modelling approach

BACKGROUND

Leprosy is an infectious disease caused by Mycobacterium leprae and remains a source of preventable disability if left undetected. Case detection delay is an important epidemiological indicator for progress in interrupting transmission and preventing disability in a community. However, no standard method exists to effectively analyse and interpret this type of data. In this study, we aim to evaluate the characteristics of leprosy case detection delay data and select an appropriate model for the variability of detection delays based on the best fitting distribution type.

METHODS

Two sets of leprosy case detection delay data were evaluated: a cohort of 181 patients from the post exposure prophylaxis for leprosy (PEP4LEP) study in high endemic districts of Ethiopia, Mozambique, and Tanzania; and self-reported delays from 87 individuals in 8 low endemic countries collected as part of a systematic literature review. Bayesian models were fit to each dataset to assess which probability distribution (log-normal, gamma or Weibull) best describes variation in observed case detection delays using leave-one-out cross-validation, and to estimate the effects of individual factors.

RESULTS

For both datasets, detection delays were best described with a log-normal distribution combined with covariates age, sex and leprosy subtype [expected log predictive density (ELPD) for the joint model: -1123.9]. Patients with multibacillary (MB) leprosy experienced longer delays compared to paucibacillary (PB) leprosy, with a relative difference of 1.57 [95% Bayesian credible interval (BCI): 1.14-2.15]. Those in the PEP4LEP cohort had 1.51 (95% BCI: 1.08-2.13) times longer case detection delay compared to the self-reported patient delays in the systematic review.

CONCLUSIONS

The log-normal model presented here could be used to compare leprosy case detection delay datasets, including PEP4LEP where the primary outcome measure is reduction in case detection delay. We recommend the application of this modelling approach to test different probability distributions and covariate effects in studies with similar outcomes in the field of leprosy and other skin-NTDs.

Leprosy and cutaneous leishmaniasis affecting the same individuals: A retrospective cohort analysis in a hyperendemic area in Brazil

Background

Leprosy and cutaneous leishmaniasis (CL) are neglected tropical diseases (NTDs) affecting the skin. Their control is challenging but the integration of skin NTDs control programs is recommended to improve timely detection and treatment. However, little is known about the occurrence of leprosy and CL in the same individuals, and what are the characteristics of such patients. This study aimed to identify and characterize patients diagnosed with both leprosy and CL (i.e., outcome) in the hyperendemic state of Mato Grosso, Brazil. Also, we investigated the demographic risk factors associated with the period between the diagnosis of both diseases.

Methodology/principal findings

A retrospective cohort study was conducted with patients diagnosed between 2008 and 2017. From the leprosy (n = 28,204) and CL (n = 24,771) databases of the national reporting system, 414 (0.8%; 414/52,561) patients presenting both diseases were identified through a probabilistic linkage procedure. This observed number was much higher than the number of patients that would be expected by chance alone (n = 22). The spatial distribution of patients presenting the outcome was concentrated in the North and Northeast mesoregions of the state. Through survival analysis, we detected that the probability of a patient developing both diseases increased over time from 0.2% in the first year to 1.0% within seven years. Further, using a Cox model we identified male sex (HR: 2.3; 95% CI: 1.7–2.9) and low schooling level (HR: 1.5; 95% CI: 1.2–1.9) as positively associated with the outcome. Furthermore, the hazard of developing the outcome was higher among individuals aged 40–55 years.

Conclusions/significance

Leprosy and CL are affecting the same individuals in the area. Integration of control policies for both diseases will help to efficiently cover such patients. Measures should be focused on timely diagnosis by following-up patients diagnosed with CL, active case detection, and training of health professionals.

Leprosy and cutaneous leishmaniasis (CL) are neglected tropical diseases (NTDs) that usually affect poor populations in the same geographical areas. Both affect the skin and can cause physical disability and disfigurement resulting in discrimination. Both diseases occur at hyperendemic levels in several regions of Brazil. The integration of skin NTDs control programs may be a way to improve timely detection and treatment. However, little is known about the occurrence of leprosy and CL in the same individuals, and what are the characteristics of these patients. For the Brazilian state of Mato Grosso, we identified 414 patients diagnosed with leprosy and CL between 2008 and 2017, spatially concentrated mainly in the North and Northeast mesoregions. The individual probability of developing both diseases increased from 0.2% to 1.0% within seven years. Male sex, being in the 40–55 years age group, and low levels of schooling were the risk factors positively associated with the time interval between the diagnosis of both diseases. These findings may inform the implementation of integrated leprosy and CL control policies focused on timely diagnosis. A sustainable integration requires continuous measures, such as the follow-up of patients, active case detection, training of health professionals, besides financial and political support.

Estimating underreporting of leprosy in Brazil using a Bayesian approach

BACKGROUND

Leprosy remains concentrated among the poorest communities in low-and middle-income countries and it is one of the primary infectious causes of disability. Although there have been increasing advances in leprosy surveillance worldwide, leprosy underreporting is still common and can hinder decision-making regarding the distribution of financial and health resources and thereby limit the effectiveness of interventions. In this study, we estimated the proportion of unreported cases of leprosy in Brazilian microregions.

METHODOLOGY/PRINCIPAL FINDINGS

Using data collected between 2007 to 2015 from each of the 557 Brazilian microregions, we applied a Bayesian hierarchical model that used the presence of grade 2 leprosy-related physical disabilities as a direct indicator of delayed diagnosis and a proxy for the effectiveness of local leprosy surveillance program. We also analyzed some relevant factors that influence spatial variability in the observed mean incidence rate in the Brazilian microregions, highlighting the importance of socioeconomic factors and how they affect the levels of underreporting. We corrected leprosy incidence rates for each Brazilian microregion and estimated that, on average, 33,252 (9.6%) new leprosy cases went unreported in the country between 2007 to 2015, with this proportion varying from 8.4% to 14.1% across the Brazilian States.

CONCLUSIONS/SIGNIFICANCE

The magnitude and distribution of leprosy underreporting were adequately explained by a model using Grade 2 disability as a marker for the ability of the system to detect new missing cases. The percentage of missed cases was significant, and efforts are warranted to improve leprosy case detection. Our estimates in Brazilian microregions can be used to guide effective interventions, efficient resource allocation, and target actions to mitigate transmission.