Mapping the baseline prevalence of lymphatic filariasis across Nigeria

Heterogeneity in elimination efforts could increase the risk of resurgence of lymphatic filariasis in Madagascar

BACKGROUND

Progress in lymphatic filariasis (LF) elimination is spatially heterogeneous in many endemic countries, which may lead to resurgence in areas that have achieved elimination. Understanding the drivers and consequences of such heterogeneity could help inform strategies to reach global LF elimination goals by 2030. This study assesses whether differences in age-specific compliance with mass drug administration (MDA) could explain LF prevalence patterns in southeastern Madagascar and explores how spatial heterogeneity in prevalence and age-specific MDA compliance may affect the risk of LF resurgence after transmission interruption.

METHODOLOGY

We used LYMFASIM model with parameters in line with the context of southeastern Madagascar and explored a wide range of scenarios with different MDA compliance for adults and children (40-100%) to estimate the proportion of elimination, non-elimination and resurgence events associated with each scenario. Finally, we evaluated the risk of resurgence associated with different levels of migration (2-6%) from surrounding districts combined with varying levels of LF microfilaria (mf) prevalence (0-24%) during that same study period.

RESULTS

Differences in MDA compliance between adults and children better explained the observed heterogeneity in LF prevalence for these age groups than differences in exposure alone. The risk of resurgence associated with differences in MDA compliance scenarios ranged from 0 to 19% and was highest when compliance was high for children (e.g. 90%) and low for adults (e.g. 50%). The risk of resurgence associated with migration was generally higher, exceeding 60% risk for all the migration levels explored (2-6% per year) when mf prevalence in the source districts was between 9% and 20%.

CONCLUSION

Gaps in the implementation of LF elimination programme can increase the risk of resurgence and undermine elimination efforts. In Madagascar, districts that have not attained elimination pose a significant risk for those that have achieved it. More research is needed to help guide LF elimination programme on the optimal strategies for surveillance and control that maximize the chances to sustain elimination and avoid resurgence.

Towards Understanding the Microepidemiology of Lymphatic Filariasis at the Community Level in Ghana

Studies on the distribution of lymphatic filariasis (LF) have mostly focused on reporting prevalence at the community level and distribution at the district levels. Understanding the distribution patterns at community levels may help in designing surveillance strategies. This study aimed to characterize the spatial distribution of LF infections in four hotspot communities in Ghana. The research, involving 252 participants, collected demographic data, mass drug administration (MDA) information, household GPS coordinates, and antigen detection test results. The LF prevalence varied significantly among the communities, with Asemda having the highest (33.33%) and Mempeasem having the lowest (4.44%). Females had lower odds of infection than males (OR = 2.67, p = 0.003 CI: 1.39-5.13). Spatial analysis using kernel density, Anselin Local Moran's, Getis-Ord Gi models, Ordinary Least Squares, and Geographic Weighted Regression revealed mixed patterns of spatial autocorrelation. This study identified LF hotspots, indicating clusters of high or low prevalence with some areas showing disparities between MDA coverage and LF positivity rates. Despite these hotspots, the overall distribution of LF appeared random, suggesting the importance of purposeful sampling in surveillance activities. These findings contribute valuable insights into the micro-epidemiology of LF, emphasizing the need for community-specific investigations to understand the factors influencing the effectiveness of MDA programs in controlling filarial infections. The study highlights the importance of refining surveillance strategies based on community-level distribution patterns.

A review of epidemiology of lymphatic filariasis in Nigeria

Lymphatic filariasis is a neglected tropical disease that affects the lymphatic system of humans. The major etiologic agent is a nematode called Wuchereria bancrofti, but Brugia malayi and Brugia timoriare sometimes encountered as causative agents. Mosquitoes are the vectors while humans the definitive hosts respectively. The burden of the disease is heavier in Nigeria than in other endemic countries in Africa. This occurs with increasing morbidity and mortality at different locations within the country, the World Health Organization recommended treatments for lymphatic filariasis include the use of Albendazole (400mg) twice per year in co-endemic areas with loa loa, Ivermectin (200mcg/kg) in combination with Albendazole (400mg) in areas that are co-endemic with onchocerciasis, ivermectin (200mcg/kg) with diethylcarbamazine citrate (DEC) (6mg/kg) and albendazole (400mg) in areas without onchocerciasis. This paper covered a systematic review, meta-analysis, and scoping review on lymphatic filariasis in the respective geopolitical zones within the country. The literature used was obtained through online search engines including PubMed and Google Scholar with the heading "lymphatic filariasis in the name of the state", Nigeria. This review revealed an overall prevalence of 11.18% with regional spread of Northwest (1.59%), North Central and North East, (4.52%), South West (1.26%), and South-South with South East (3.81%) prevalence. The disease has been successfully eliminated in Argungu local government areas (LGAs) of Kebbi State, Plateau, and Nasarawa States respectively. Most clinical manifestations (31.12%) include hydrocele, lymphedema, elephantiasis, hernia, and dermatitis. Night blood samples are appropriate for microfilaria investigation. Sustained MDAs, the right testing methods, early treatment of infected cases, and vector control are useful for the elimination of lymphatic filariasis for morbidity management and disability prevention in the country. Regional control strategies, improved quality monitoring of surveys and intervention programs with proper records of morbidity and disability requiring intervention are important approaches for the timely elimination of the disease in Nigeria.

Integration of services for Neglected Tropical Diseases and mental health in Nigeria: development of a practical model informed by international recommendations, contextual factors and service-user perspectives

BACKGROUND

Mental health care is now recognised as essential for people affected by NTDs, but accessible services are rare. This paper presents results of a prevalence study for depression and anxiety among people living with leprosy and lymphatic filariasis, and collation of user perspectives on needs and priorities for a new service.

METHODS

Prevalence of mental conditions was carried out with 141 people living with leprosy and lymphatic filariasis and matched controls. Those who screened positive for depression or anxiety were interviewed in a qualitative study to understand their experiences of living with the conditions, and what their priorities would be for services and support. Results contributed to the process of developing a contextually adapted collaborative care model for implementation in the primary care system in Nigeria, using a Theory of Change approach.

RESULTS

We found high rates of depression, anxiety, and reduced wellbeing, with strong correlation across measures. The qualitative study revealed experiences of stigma and exclusion, and concern for financial and economic needs, and a desire for provision of free services and support for livelihoods.

CONCLUSION

Services should be designed with good understanding of local needs and service user priorities.

CONTEXTE

Les soins de santé mentale sont désormais reconnus comme essentiels pour les personnes touchées par les MTN, mais les services accessibles sont rares. Cet article présente les résultats d'une étude de prévalence de la dépression et de l'anxiété chez les personnes vivant avec la lèpre et la filariose lymphatique, ainsi que la collecte des points de vue des utilisateurs sur les besoins et les priorités d'un nouveau service.

MÉTHODES UTILISÉES

Une étude de prévalence des troubles mentaux a été menée auprès de 141 personnes vivant avec la lèpre et la filariose lymphatique et de témoins appariés. Celles qui ont été dépistées positives pour la dépression ou l'anxiété ont été interrogées dans le cadre d'une étude qualitative afin de comprendre leur expérience de la vie avec ces maladies et leurs priorités en matière de services et de soutien. Les résultats ont contribué au processus d'élaboration d'un modèle de soins collaboratifs adapté au contexte et destiné à être mis en œuvre dans le système de soins primaires au Nigeria, à l'aide d'une approche fondée sur la théorie du changement.

RÉSULTATS

Nous avons constaté des taux élevés de dépression, d'anxiété et de diminution du bien-être, avec une forte corrélation entre les mesures. L'étude qualitative a révélé des expériences de stigmatisation et d'exclusion, des préoccupations concernant les besoins financiers et économiques, ainsi qu'un désir de services gratuits et de soutien aux moyens de subsistance.

CONCLUSION

Les services doivent être conçus en tenant compte des besoins locaux et des priorités des utilisateurs.

ANTECEDENTES

Actualmente se reconoce que la atención de salud mental es esencial para las personas afectadas por ETD, pero los servicios accesibles son escasos. los servicios accesibles son escasos. Este documento presenta los resultados de un estudio de prevalencia de depresión y ansiedad entre las personas que viven con lepra y filariasis linfática, y las perspectivas de los usuarios sobre las necesidades y prioridades de un nuevo servicio.

MÉTODOS

Se realizó un estudio de prevalencia de trastornos mentales con 141 personas que vivían con lepra y filariasis linfática y controles emparejados. Los que dieron positivo en depresión o ansiedad fueron entrevistados en un estudio cualitativo para conocer sus de vivir con estas enfermedades y cuáles serían sus prioridades en cuanto a servicios y apoyo. servicios y apoyo. Los resultados contribuyeron al proceso de desarrollo de un modelo de atención para su aplicación en el sistema de atención primaria de Nigeria, utilizando un enfoque basado en la Teoría del Cambio.

RESULTADOS

Encontramos altas tasas de depresión, ansiedad y reducción del bienestar, con una fuerte correlación entre las medidas. correlación entre las medidas. El estudio cualitativo reveló experiencias de estigmatización y de estigmatización y exclusión, preocupación por las necesidades financieras y servicios gratuitos y apoyo a los medios de subsistencia.

CONCLUSIÓN

Los servicios deben diseñarse teniendo en cuenta las necesidades locales y las prioridades de los usuarios de los usuarios.

Entomological surveillance reveals transmission of malaria but not lymphatic filariasis in two communities in North-West Nigeria

Malaria and lymphatic filariasis (LF) are two serious public health challenges in sub-Saharan Africa, and both diseases are transmitted by Anopheles mosquitoes. Successful control of both diseases requires detailed information on transmission dynamics; thus, this study investigated malaria and LF transmission indices in two (2) communities (Jidawa and Kargo) in North-West Nigeria. Anopheles mosquitoes were sampled from twenty-five (25) randomly selected houses from each of the two communities using pyrethrum spray collection (PSC). The samples were identified morphologically and molecularly characterised using polymerase chain reaction (PCR). Human biting rate (HBR), indoor resting density (IRD), sporozoite rate (SR) and entomological inoculation rate (EIR) were calculated using standard formulae. The thorax region of the collected samples were dissected and smeared; then, Plasmodium and Wuchereria bancrofti parasites were identified using microscopy. A total of 2417 Anopheles mosquitoes were collected, and all were identified morphologically as An. gambiae s.l. Further molecular identification of sibling species revealed that An. gambiae and An. arabiensis were the only sibling species present. A total of 818 Anopheles mosquitoes were screened for Plasmodium and Wuchereria bancrofti parasites. A total of 180 samples were positive for Plasmodium parasites (Jidawa = 151; Kargo = 29), and none was positive for W. bancrofti (0%). Result of entomological indices for malaria transmission showed that indoor resting density was higher in Jidawa (10 mosquitoes/room/night) while human biting rate (2.07 bites/person/night), sporozoite rate (29.3%) and entomological inoculation rate (0.61) were higher in Kargo. In total, 35.2% of the samples were blood-fed while 67.4% were parous. There is active transmission of malaria in the two communities but not LF, suggesting the effectiveness of mass drug administration for LF. Concerted efforts should be focused on malaria control as transmission of the disease persists.

Geospatial modelling of lymphatic filariasis and malaria co-endemicity in Nigeria

BACKGROUND

Lymphatic filariasis (LF) and malaria are important vector-borne diseases that are co-endemic throughout Nigeria. These infections are transmitted by the same mosquito vector species in Nigeria and their transmission is similarly influenced by climate and sociodemographic factors. The goal of this study was to assess the relationship between the geospatial distribution of both infections in Nigeria to better coordinate interventions.

METHODS

We used national survey data for malaria from the Demographic and Health Survey dataset and site-level LF mapping data from the Nigeria Lymphatic Filariasis Control Programme together with a suite of predictive climate and sociodemographic factors to build geospatial machine learning models. These models were then used to produce continuous gridded maps of both infections throughout Nigeria.

RESULTS

The R2 values for the LF and malaria models were 0.68 and 0.59, respectively. Also, the correlation between pairs of observed and predicted values for LF and malaria models were 0.69 (95% confidence interval [CI] 0.61 to 0.79; p<0.001) and 0.61 (95% CI 0.52 to 0.71; p<0.001), respectively. However, we observed a very weak positive correlation between overall overlap of LF and malaria distribution in Nigeria.

CONCLUSIONS

The reasons for this counterintuitive relationship are unclear. Differences in transmission dynamics of these parasites and vector competence may contribute to differences in the distribution of these co-endemic diseases.

Geospatial distribution and predictive modeling of onchocerciasis in Ogun State, Nigeria

Onchocerciasis caused by infection with Onchocerca volvulus is a disease of public health importance and is highly associated with disability. As Nigeria is aiming at eliminating onchocerciasis by 2030, there is a need to develop newer tools to map disease prevalence and identify environmental factors driving disease prevalence, even in places that have not been previously targeted for preventive chemotherapy. This study produced predictive risk-maps of onchocerciasis in Ogun State. Georeferenced onchocerciasis infection data obtained from a cross-sectional survey at 32 locations between March and July 2015 together with remotely-sensed environmental data were analyzed using Ecological Niche Models (ENM). A total of 107 field occurrence points for O. volvulus infection were recorded. A total of 43 positive occurrence points were used for modelling. ENMs were used to estimate the current geographic distribution of O. volvulus in Ogun State. Maximum Entropy distribution modeling (MaxEnt) was used for predicting the potential suitable habitats, using a portion of the occurrence records. A total of 19 environmental variables were used to model the potential geographical distribution area under current climatic conditions. Empirical prevalence of 9.3% was recorded in this study. The geospatial distribution of infection revealed that all communities in Odeda Local Government Area (a peri-urban LGA) showed remarkably high prevalence compared with other LGAs. The predicted high-risk areas (probability > 0.8) of O. volvulus infection were all parts of Odeda, Abeokuta South, and Abeokuta North, southern part of Imeko-Afon, a large part of Yewa North, some parts of Ewekoro and Obafemi-Owode LGAs. The estimated prevalence for these regions were >60% (between 61% and 100%). As predicted, O. volvulus occurrence showed a positive association with variables reflecting precipitation in Ogun State. Our predictive risk-maps has provided useful information for the elimination of onchocerciais, by identifying priority areas for delivery of intervention in Ogun State, Nigeria.

Persistence of onchocerciasis in villages in Enugu and Ogun states in Nigeria following many rounds of mass distribution of ivermectin

Background

Onchocerciasis is endemic in most local government areas (LGAs) in Enugu and Ogun states. Most meso- and hyper-endemic LGAs have received many rounds of ivermectin mass drug administration (MDA). This study aimed to determine the current prevalence of onchocerciasis in villages in Enugu and Ogun states that were formerly highly endemic and to assess progress toward elimination of the infection in areas believed to be at high risk for persistence.

Methods

Cross-sectional community surveys were conducted 8 to 12 months after the last round of MDA in 16 villages (6 in Enugu state and 10 in Ogun state) in individuals aged ≥ 18 years. Study participants were examined for the presence of palpable subcutaneous nodules. Skin snips from the posterior iliac crests were used to assess microfiladermia (Mf) prevalence and density.

Results

643 subjects were palpated for nodules and 627 individuals (225 in Enugu state; 402 in Ogun state) provided skin snips. Nodule prevalence in the study villages ranged from 42 to 66.7% in Enugu state and from 0 to 25.0% in Ogun state. Mf prevalence in the Enugu and Ogun study villages ranged from 32 to 51.1% and 0 to 28.6%, respectively. Geometric mean skin Mf density in surveyed Enugu state villages ranged between 1 and 3.1 Mf/mg; these values were < 1 Mf/mg in all but one community in Ogun state villages.

Conclusion

Results from this study show that onchocerciasis persists in adults in many villages in Enugu and Ogun states despite many prior rounds of ivermectin MDA. Prevalence was higher in villages surveyed in Enugu than in Ogun. Low Mf densities suggest the MDA program is working well to reduce disease, but more time will be required to reach the elimination goal.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12879-022-07811-7.

Linear and Machine Learning modelling for spatiotemporal disease predictions: Force-of-Infection of Chagas disease

Background

Chagas disease is a long-lasting disease with a prolonged asymptomatic period. Cumulative indices of infection such as prevalence do not shed light on the current epidemiological situation, as they integrate infection over long periods. Instead, metrics such as the Force-of-Infection (FoI) provide information about the rate at which susceptible people become infected and permit sharper inference about temporal changes in infection rates. FoI is estimated by fitting (catalytic) models to available age-stratified serological (ground-truth) data. Predictive FoI modelling frameworks are then used to understand spatial and temporal trends indicative of heterogeneity in transmission and changes effected by control interventions. Ideally, these frameworks should be able to propagate uncertainty and handle spatiotemporal issues.

Methodology/principal findings

We compare three methods in their ability to propagate uncertainty and provide reliable estimates of FoI for Chagas disease in Colombia as a case study: two Machine Learning (ML) methods (Boosted Regression Trees (BRT) and Random Forest (RF)), and a Linear Model (LM) framework that we had developed previously. Our analyses show consistent results between the three modelling methods under scrutiny. The predictors (explanatory variables) selected, as well as the location of the most uncertain FoI values, were coherent across frameworks. RF was faster than BRT and LM, and provided estimates with fewer extreme values when extrapolating to areas where no ground-truth data were available. However, BRT and RF were less efficient at propagating uncertainty.

Conclusions/significance

The choice of FoI predictive models will depend on the objectives of the analysis. ML methods will help characterise the mean behaviour of the estimates, while LM will provide insight into the uncertainty surrounding such estimates. Our approach can be extended to the modelling of FoI patterns in other Chagas disease-endemic countries and to other infectious diseases for which serosurveys are regularly conducted for surveillance.

Metrics such as the per susceptible rate of infection acquisition (Force-of-Infection) are crucial to understand the current epidemiological situation and the impact of control interventions for long-lasting diseases in which the infection event might have occurred many years previously, such as Chagas disease. FoI values are estimated from serological age profiles, often obtained in a few locations. However, when using predictive models to estimate the FoI over time and space (including areas where serosurveys had not been conducted), methods able to handle and propagate uncertainty must be implemented; otherwise, overconfident predictions may be obtained. Although Machine Learning (ML) methods are powerful tools, they may not be able to entirely handle this challenge. Therefore, the use of ML must be considered in relation to the aims of the analyses. ML will be more relevant to characterise the central trends of the estimates while Linear Models will help identify areas where further serosurveys should be conducted to improve the reliability of the predictions. Our approaches can be used to generate FoI predictions in other Chagas disease-endemic countries as well as in other diseases for which serological surveillance data are collected.

Geospatial modeling of pre-intervention nodule prevalence of Onchocerca volvulus in Ethiopia as an aid to onchocerciasis elimination

Background

Onchocerciasis is a neglected tropical filarial disease transmitted by the bites of blackflies, causing blindness and severe skin lesions. The change in focus for onchocerciasis management from control to elimination requires thorough mapping of pre-control endemicity to identify areas requiring interventions and to monitor progress. Onchocerca volvulus nodule prevalence in sub-Saharan Africa is spatially continuous and heterogeneous, and highly endemic areas may contribute to transmission in areas of low endemicity or vice-versa. Ethiopia is one such onchocerciasis-endemic country with heterogeneous O. volvulus nodule prevalence, and many districts are still unmapped despite their potential for onchocerciasis transmission.

Methodology/Principle findings

A Bayesian geostatistical model was fitted for retrospective pre-intervention nodule prevalence data collected from 916 unique sites and 35,077 people across Ethiopia. We used multiple environmental, socio-demographic, and climate variables to estimate the pre-intervention prevalence of O. volvulus nodules across Ethiopia and to explore their relationship with prevalence. Prevalence was high in southern and northwestern Ethiopia and low in Ethiopia’s central and eastern parts. Distance to the nearest river (RR: 0.9850, 95% BCI: 0.9751–0.995), precipitation seasonality (RR: 0.9837, 95% BCI: 0.9681–0.9995), and flow accumulation (RR: 0.9586, 95% BCI: 0.9321–0.9816) were negatively associated with O. volvulus nodule prevalence, while soil moisture (RR: 1.0218, 95% BCI: 1.0135–1.0302) was positively associated. The model estimated the number of pre-intervention cases of O. volvulus nodules in Ethiopia to be around 6.48 million (95% BCI: 3.53–13.04 million).

Conclusions/Significance

Nodule prevalence distribution was correlated with habitat suitability for vector breeding and associated biting behavior. The modeled pre-intervention prevalence can be used as a guide for determining priorities for elimination mapping in regions of Ethiopia that are currently unmapped, most of which have comparatively low infection prevalence.

Areas with unknown onchocerciasis endemicity may pose a threat to eliminating transmission because they may re-introduce onchocerciasis to areas where interventions have been successful. Additionally, because vectors (and thus Onchocerca volvulus transmission) have specific ecological requirements for growth and development, changes in these ecological factors due to human activities (deforestation, modification of river flows by dam construction, climate change) might change patterns of parasite transmission and endemicity. To estimate the impact of environmental changes, we must first identify ecological factors determining prevalence. We have employed Bayesian geostatistical modeling to create a nationwide O. volvulus nodule prevalence map for Ethiopia based on pre-intervention nodule prevalence data and have explored the effect of environmental variables on nodule prevalence. We estimated the number of pre-intervention cases of nodules and associated uncertainty in previously unmapped areas of Ethiopia to identify areas that need additional data to increase the prediction accuracy. Hydrological variables such as distance to the nearest river, precipitation seasonality, soil moisture, and flow accumulation are associated significantly with O. volvulus nodule prevalence. We show that the spatial distribution of nodule prevalence can be estimated based on ecological data and that predicted prevalence can be used as a guide to prioritize pre-intervention mapping.

Artificial intelligence and lymphedema: State of the art

Background

Lymphedema practice is facing many challenges. Some of these challenges include eradication of tropical lymphedema, preclinical diagnosis of cancer-related lymphedema, and delivery of appropriate individualized care. The past two decades have witnessed an increasing implementation of artificial intelligence (AI) in health-care services. The nature of the challenges facing the lymphedema practice is suitable for AI applications.

Aim

The aim of this study was to explore the current AI applications in lymphedema prevention, diagnosis, and management and investigate the potential future applications.

Methods and Results

Four databases were searched: PubMed, Scopus, Web of Science, and EMBASE. We used the Preferred Reporting Items for Systematic Reviews and Meta-Analysis as our basis of organization. Our analysis showed that several domains of AI, including machine learning (ML), fuzzy models, deep learning, and robotics, were successfully implemented in lymphedema practice. ML can guide the eradication campaigns of tropical lymphedema by estimating disease prevalence and mapping the risk areas. Robotic-assisted surgery for gynecological cancer was associated with a lower risk for the lower limb lymphedema. Several feasible models were described for the early detection and diagnosis of lymphedema. The proposed models are more accurate, sensitive, and specific than current methods in practice. ML was also used to guide and monitor patients during the rehabilitation exercises.

Conclusion

AI offers a variety of solutions to the most challenging problems in lymphedema practice. Further, implementation into the practice can revolutionize many aspects of lymphedema prevention, diagnosis, and management.

Relevance to Patients

Lymphedema is a chronic debilitating disease that is affecting millions of patients. Developing new modalities for prevention, early diagnosis, and treatment are critical to improve the outcomes. AI offers a variety of solutions for some of the complexities of lymphedema management. In this systematic review, we summarize and discuss the latest AI advances in lymphedema practice.

Pyrethroid Susceptibility in Culex quinquefasciatus Say. (Diptera: Culicidae) Populations from Delta State, Niger-Delta Region, Nigeria

The development of insecticide resistance in different species of mosquitoes to Pyrethroids is a major challenge for vector-borne diseases transmitted by mosquitoes. Failure of Pyrethroids in control of mosquitoes would impact negatively on the gains recorded in control of mosquito-borne diseases in previous years. In anticipation of a country-wide deployment of Pyrethroid-treated nets for control of mosquito-borne diseases in Nigeria, this study assessed susceptibility of Culex quinquefasciatus Say. (Diptera: Culicidae) to Pyrethroids in Owhelogbo, Ejeme and Oria-Abraka communities in Delta State, Niger-Delta, Nigeria. Three to five day old Cx. quinquefasciatus were exposed to Deltamethrin (0.05%), Permethrin (0.75%), and Alphacypermethrin (0.05%) using World Health Organization bioassay method. Polymerase chain reaction (PCR) was employed in characterization of species and knockdown mutation. Results revealed that Cx. quinquefasciatus were generally susceptible (98-100%) to Deltamethrin, Permethrin, and Alphacypermethrin in the three communities with the exception of Owhelogbo where resistance to Deltamethrin (97%) was suspected. Knockdown time to Deltamethrin (11.51, 11.23, and 12.68 min), Permethrin (28.75, 13.26, and 14.49 min), and Alphacypermethrin (15.07, 12.50, and 13.03 min) were considerably low for Owhelogbo, Ejeme, and Oria-Abraka Cx. quinquefasciatus populations, respectively. Species identification result showed that all amplified samples were Cx. quinquefasciatus; however, no kdr allele was found in the three populations. Deployment of pyrethroid-treated nets for control of mosquito-borne diseases in Niger-Delta region of Nigeria is capable of reducing burden of diseases transmitted by Cx. quinquefasciatus as well as addressing nuisance value of the vector; however, caution must be entertained so as not to increase selection pressure thereby aiding resistance development.

Progress towards onchocerciasis elimination in Côte d'Ivoire: A geospatial modelling study

Background

Côte d’Ivoire has had 45 years of intervention for onchocerciasis by vector control (from 1975 to 1991), ivermectin mass drug administration (MDA) (from 1992 to 1994) and community directed treatment with ivermectin (CDTi) from 1995 to the present. We modeled onchocerciasis endemicity during two time periods that correspond to the scale up of vector control and ivermectin distribution, respectively. This analysis illustrates progress towards elimination during these periods, and it has identified potential hotspots areas that are at risk for ongoing transmission.

Methods and findings

The analysis used Ministry of Health skin snip microfilaria (MF) prevalence and intensity data collected between 1975 and 2016. Socio-demographic and environmental factors were incorporated into a predictive, machine learning algorithm to create continuous maps of onchocerciasis endemicity. Overall predicted mean MF prevalence decreased from 51.8% circa 1991 to 3.9% circa 2016. The model predicted infection foci with higher prevalence in the southern region of the country. Predicted mean community MF load (CMFL) decreased from 10.1MF/snip circa 1991 to 0.1MF/snip circa 2016. Again, the model predicts foci with higher Mf densities in the southern region. For assessing model performance, the root mean squared error and R² values were 1.14 and 0.62 respectively for a model trained with data collected prior to 1991, and 1.28 and 0.57 for the model trained with infection survey data collected later, after the introduction of ivermectin. Finally, our models show that proximity to permanent inland bodies of water and altitude were the most informative variables that correlated with onchocerciasis endemicity.

Conclusion/Significance

This study further documents the significant reduction of onchocerciasis infection following widespread use of ivermectin for onchocerciasis control in Côte d’Ivoire. Maps produced predict areas at risk for ongoing infection and transmission. Onchocerciasis might be eliminated in Côte d’Ivoire in the future with a combination of sustained CDTi with high coverage, active surveillance, and close monitoring for persistent infection in previously hyper-endemic areas.

Côte d’Ivoire is endemic for onchocerciasis (also known as “river blindness”). This neglected tropical disease is transmitted by biting black flies that breed in fast flowing rivers. From 1975 to 1991, onchocerciasis control was based on weekly aerial spraying of the insecticide temephos, on black fly breeding sites. Vector control, however, was mostly focused on the northern and central parts of the country. From 1992 to present, mass treatment with ivermectin was implemented in all endemic areas, including forested regions in the south. Here we present the first geospatial estimates of onchocerciasis endemicity over time. Using the machine learning algorithm quantile regression forest, we implemented models to: identify important socio-demographic and environmental factors that correlate with onchocerciasis infection; predict the prevalence and density of infection in areas without ground-truth data; delineate remaining infection hotspots. Our results show that Côte d’Ivoire has made very significant progress in reducing infection parameters over time, and they may help to inform future interventions to achieve the goal of onchocerciasis elimination in Côte d’Ivoire.