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Sékré JBK, Ouattara M, Diakité NR, Bassa FK, Assaré RK, Kouadio JN, Coulibaly G, Loukouri A, Orsot MN, Utzinger J, N’Goran EK. Effectiveness of Three Sampling Approaches for Optimizing Mapping and Preventive Chemotherapy against Schistosoma mansoni in the Western Part of Côte d'Ivoire. Trop Med Infect Dis 2024; 9:159. [PMID: 39058201 PMCID: PMC11281647 DOI: 10.3390/tropicalmed9070159] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/29/2024] [Revised: 06/30/2024] [Accepted: 07/10/2024] [Indexed: 07/28/2024] Open
Abstract
The elimination of schistosomiasis as a public health problem by 2030 is one of the main goals put forth in the World Health Organization's roadmap for neglected tropical diseases. This study aimed to compare different sampling approaches to guide mapping and preventive chemotherapy. A cross-sectional parasitological survey was conducted from August to September 2022 in the health districts of Biankouma, Ouaninou, and Touba in the western part of Côte d'Ivoire. The prevalence and intensity of Schistosoma mansoni infection were assessed in children aged 5-14 years using three sampling approaches. The first approach involved a random selection of 50% of the villages in the health districts. The second approach involved a random selection of half of the villages selected in approach 1, thus constituting 25% of the villages in the health district. The third approach consisted of randomly selecting 15 villages from villages selected by approach 2 in each health district. The overall prevalence of S. mansoni was 23.5% (95% confidence interval (CI): 19.9-27.6%), 21.6% (95% CI: 17.1-26.8%), and 18.3% (95% CI: 11.9-27.1%) with the first, second, and third approach, respectively. The respective geometric mean S. mansoni infection intensity was 117.9 eggs per gram of stool (EPG) (95% CI: 109.3-127.3 EPG), 104.6 EPG (95% CI: 93.8-116.6 EPG), and 94.6 EPG (95% CI 79.5-112.7 EPG). We conclude that, although randomly sampling up to 50% of villages in a health district provides more precise population-based prevalence and intensity measures of S. mansoni, randomly selecting only 15 villages in a district characterized by low heterogeneity provides reasonable estimates and is less costly.
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Affiliation(s)
- Jean-Baptiste K. Sékré
- Unité de Formation et de Recherche Biosciences, Université Félix Houphouët-Boigny, Abidjan 22 BP 582, Côte d’Ivoire; (M.O.); (N.R.D.); (F.K.B.); (R.K.A.); (J.N.K.); (G.C.); (A.L.); (M.N.O.); (E.K.N.)
| | - Mamadou Ouattara
- Unité de Formation et de Recherche Biosciences, Université Félix Houphouët-Boigny, Abidjan 22 BP 582, Côte d’Ivoire; (M.O.); (N.R.D.); (F.K.B.); (R.K.A.); (J.N.K.); (G.C.); (A.L.); (M.N.O.); (E.K.N.)
- Centre Suisse de Recherches Scientifiques en Côte d’Ivoire, Abidjan 01 BP 1303, Côte d’Ivoire
| | - Nana R. Diakité
- Unité de Formation et de Recherche Biosciences, Université Félix Houphouët-Boigny, Abidjan 22 BP 582, Côte d’Ivoire; (M.O.); (N.R.D.); (F.K.B.); (R.K.A.); (J.N.K.); (G.C.); (A.L.); (M.N.O.); (E.K.N.)
- Centre Suisse de Recherches Scientifiques en Côte d’Ivoire, Abidjan 01 BP 1303, Côte d’Ivoire
| | - Fidèle K. Bassa
- Unité de Formation et de Recherche Biosciences, Université Félix Houphouët-Boigny, Abidjan 22 BP 582, Côte d’Ivoire; (M.O.); (N.R.D.); (F.K.B.); (R.K.A.); (J.N.K.); (G.C.); (A.L.); (M.N.O.); (E.K.N.)
- Centre Suisse de Recherches Scientifiques en Côte d’Ivoire, Abidjan 01 BP 1303, Côte d’Ivoire
| | - Rufin K. Assaré
- Unité de Formation et de Recherche Biosciences, Université Félix Houphouët-Boigny, Abidjan 22 BP 582, Côte d’Ivoire; (M.O.); (N.R.D.); (F.K.B.); (R.K.A.); (J.N.K.); (G.C.); (A.L.); (M.N.O.); (E.K.N.)
- Centre Suisse de Recherches Scientifiques en Côte d’Ivoire, Abidjan 01 BP 1303, Côte d’Ivoire
| | - Jules N. Kouadio
- Unité de Formation et de Recherche Biosciences, Université Félix Houphouët-Boigny, Abidjan 22 BP 582, Côte d’Ivoire; (M.O.); (N.R.D.); (F.K.B.); (R.K.A.); (J.N.K.); (G.C.); (A.L.); (M.N.O.); (E.K.N.)
- Centre Suisse de Recherches Scientifiques en Côte d’Ivoire, Abidjan 01 BP 1303, Côte d’Ivoire
| | - Gaoussou Coulibaly
- Unité de Formation et de Recherche Biosciences, Université Félix Houphouët-Boigny, Abidjan 22 BP 582, Côte d’Ivoire; (M.O.); (N.R.D.); (F.K.B.); (R.K.A.); (J.N.K.); (G.C.); (A.L.); (M.N.O.); (E.K.N.)
- Centre Suisse de Recherches Scientifiques en Côte d’Ivoire, Abidjan 01 BP 1303, Côte d’Ivoire
| | - Agodio Loukouri
- Unité de Formation et de Recherche Biosciences, Université Félix Houphouët-Boigny, Abidjan 22 BP 582, Côte d’Ivoire; (M.O.); (N.R.D.); (F.K.B.); (R.K.A.); (J.N.K.); (G.C.); (A.L.); (M.N.O.); (E.K.N.)
| | - Mathieu N. Orsot
- Unité de Formation et de Recherche Biosciences, Université Félix Houphouët-Boigny, Abidjan 22 BP 582, Côte d’Ivoire; (M.O.); (N.R.D.); (F.K.B.); (R.K.A.); (J.N.K.); (G.C.); (A.L.); (M.N.O.); (E.K.N.)
| | - Jürg Utzinger
- Swiss Tropical and Public Health Institute, Kreuzstrasse 2, CH-4123 Allschwil, Switzerland;
- University of Basel, Petersplatz 1, CH-4003 Basel, Switzerland
| | - Eliézer K. N’Goran
- Unité de Formation et de Recherche Biosciences, Université Félix Houphouët-Boigny, Abidjan 22 BP 582, Côte d’Ivoire; (M.O.); (N.R.D.); (F.K.B.); (R.K.A.); (J.N.K.); (G.C.); (A.L.); (M.N.O.); (E.K.N.)
- Centre Suisse de Recherches Scientifiques en Côte d’Ivoire, Abidjan 01 BP 1303, Côte d’Ivoire
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Kargbo-Labour I, Redwood-Sawyerr V, Conteh A, Chop E, Bah MS, Koroma A, Kabia U, Klein L, Juneja S, Houck P, Reid S, Evans D, Weaver AM, Phillips AE, Zhang Y. Re-assessment of schistosomiasis in nine endemic districts with cluster sampling in Sierra Leone. Front Public Health 2024; 12:1415486. [PMID: 38932788 PMCID: PMC11199885 DOI: 10.3389/fpubh.2024.1415486] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/10/2024] [Accepted: 05/23/2024] [Indexed: 06/28/2024] Open
Abstract
Background Baseline mapping showed that schistosomiasis was highly/moderately endemic in nine districts in Sierra Leone. Mass drug administration (MDA) with praziquantel started in 2009, and after multiple rounds of treatment, an impact assessment was conducted in 2016 followed by a second re-assessment in 2022 using cluster sampling to provide more granular data for refining chiefdom (sub-district) treatment strategies. Methods On average, 20 rural villages were systematically selected per district by probability proportional to population size across the nine districts. Surveys were conducted in schools, and 24 school children aged between 5 and 14 years were randomly selected, with an equal number of boys and girls. One stool sample and one urine sample were collected per child. Two Kato-Katz slides were examined per stool for Schistosoma mansoni infection. Hemastix strips were used as a proxy for S. haematobium infection with urine filtration used for egg counts on hematuria-positive samples. Results In total, 4,736 stool samples and 4,618 urine samples were examined across 200 schools in 125 chiefdoms. Overall, the prevalence of S. mansoni was 16.3% (95% CI: 15.3-17.4%), while the overall prevalence of S. haematobium was 2.0% (95% CI: 1.6-2.4%) by hematuria. The prevalence of heavy infections for S. mansoni and S. haematobium was 1.5% (95% CI: 1.1-1.9%) and 0.02% (95% CI: 0.0-0.14%), respectively. Among 125 chiefdoms surveyed, the overall schistosomiasis prevalence was <10% in 65 chiefdoms, 10-49.9% in 47 chiefdoms, and ≥ 50% in 13 chiefdoms. There was a mixed relationship between schistosomiasis in school children and WASH access in schools. Conclusion Sierra Leone has made significant progress in reducing schistosomiasis prevalence across the country after a decade of MDA intervention. However, high prevalence remains in some hotspot chiefdoms. The next steps are for the national program to investigate and address any potential issues such as low coverage or poor knowledge of schistosomiasis risk behaviors and, where appropriate, consider broadening to community-wide treatment in hotspot chiefdoms or communities.
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Affiliation(s)
- Ibrahim Kargbo-Labour
- National Neglected Tropical Disease Control Program, Ministry of Health and Sanitation, Freetown, Sierra Leone
| | | | - Abdulai Conteh
- National Neglected Tropical Disease Control Program, Ministry of Health and Sanitation, Freetown, Sierra Leone
| | | | | | | | | | | | | | | | - Steven Reid
- Helen Keller International, New York, NY, United States
| | - Darin Evans
- United States Agency for International Development, Washington, DC, United States
| | | | | | - Yaobi Zhang
- Helen Keller International, New York, NY, United States
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Mathewson JD, van der Spek L, Mazigo HD, Kabona G, de Vlas SJ, Nshala A, Rood EJJ. Enabling targeted mass drug administration for schistosomiasis in north-western Tanzania: Exploring the use of geostatistical modeling to inform planning at sub-district level. PLoS Negl Trop Dis 2024; 18:e0011896. [PMID: 38227610 PMCID: PMC10817176 DOI: 10.1371/journal.pntd.0011896] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2023] [Revised: 01/26/2024] [Accepted: 01/02/2024] [Indexed: 01/18/2024] Open
Abstract
INTRODUCTION Schistosomiasis is a parasitic disease in Tanzania affecting over 50% of the population. Current control strategies involve mass drug administration (MDA) campaigns at the district level, which have led to problems of over- and under-treatment in different areas. WHO guidelines have called for more targeted MDA to circumvent these problems, however a scarcity of prevalence data inhibits decision makers from prioritizing sub-district areas for MDA. This study demonstrated how geostatistics can be used to inform planning for targeted MDA. METHODS Geostatistical sub-district (ward-level) prevalence estimates were generated through combining a zero-inflated poisson model and kriging approach (regression kriging). To make predictions, the model used prevalence survey data collected in 2021 of 17,400 school children in six regions of Tanzania, along with several open source ecological and socio-demographic variables with known associations with schistosomiasis. RESULTS The model results show that regression kriging can be used to effectively predict the ward level parasite prevalence of the two species of Schistosoma endemic to the study area. Kriging was found to further improve the regression model fit, with an adjusted R-squared value of 0.51 and 0.32 for intestinal and urogenital schistosomiasis, respectively. Targeted treatment based on model predictions would represent a shift in treatment away from 193 wards estimated to be over-treated to 149 wards that would have been omitted from the district level MDA. CONCLUSIONS Geostatistical models can help to support NTD program efficiency and reduce disease transmission by facilitating WHO recommended targeted MDA treatment through provision of prevalence estimates where data is scarce.
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Affiliation(s)
- Jake D. Mathewson
- Kit-Royal Tropical Institute, Epidemiology, Center for Applied Spatial Epidemiology (CASE), Amsterdam, The Netherlands
| | - Linda van der Spek
- Kit-Royal Tropical Institute, Epidemiology, Center for Applied Spatial Epidemiology (CASE), Amsterdam, The Netherlands
| | - Humphrey D. Mazigo
- School of Medicine, Department of Medical Parasitology & Entomology, Catholic University of Health and Allied Sciences, Mwanza, Tanzania
| | - George Kabona
- Ministry of Health, National Neglected Tropical Diseases Control Programme, Dodoma, Tanzania
| | - Sake J. de Vlas
- Department of Public Health, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
| | | | - Ente J. J. Rood
- Kit-Royal Tropical Institute, Epidemiology, Center for Applied Spatial Epidemiology (CASE), Amsterdam, The Netherlands
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Okoyo C, Orowe I, Onyango N, Montresor A, Mwandawiro C, Medley GF. Optimal control analysis of a transmission interruption model for the soil-transmitted helminth infections in Kenya. CURRENT RESEARCH IN PARASITOLOGY & VECTOR-BORNE DISEASES 2023; 4:100162. [PMID: 38089690 PMCID: PMC10714213 DOI: 10.1016/j.crpvbd.2023.100162] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/18/2023] [Revised: 11/26/2023] [Accepted: 11/27/2023] [Indexed: 02/12/2024]
Abstract
Kenya is among the countries endemic for soil-transmitted helminthiasis (STH) with over 66 subcounties and over 6 million individuals being at-risk of infection. Currently, the country is implementing mass drug administration (MDA) to all the at-risk groups as the mainstay control strategy. This study aimed to develop and analyze an optimal control (OC) model, from a transmission interruption model, to obtain an optimal control strategy from a mix of three strategies evaluated. The study used the Pontryagin's maximum principle to solve, numerically, the OC model. The analysis results clearly demonstrated that water and sanitation when implemented together with the MDA programme offer the best chances of eliminating these tenacious and damaging parasites. Thus, we advocate for optimal implementation of the combined mix of the two interventions in order to achieve STH elimination in Kenya, and globally, in a short implementation period of less than eight years.
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Affiliation(s)
- Collins Okoyo
- School of Mathematics, University of Nairobi, Nairobi, Kenya
- Eastern and Southern Africa Centre of International Parasite Control (ESACIPAC), Kenya Medical Research Institute (KEMRI), Nairobi, Kenya
- Department of Epidemiology, Statistics and Informatics (DESI), Kenya Medical Research Institute (KEMRI), Nairobi, Kenya
| | - Idah Orowe
- School of Mathematics, University of Nairobi, Nairobi, Kenya
| | - Nelson Onyango
- School of Mathematics, University of Nairobi, Nairobi, Kenya
| | - Antonio Montresor
- Department of Control of Neglected Tropical Diseases, World Health Organization, Geneva, Switzerland
| | - Charles Mwandawiro
- Eastern and Southern Africa Centre of International Parasite Control (ESACIPAC), Kenya Medical Research Institute (KEMRI), Nairobi, Kenya
| | - Graham F. Medley
- Faculty of Public Health and Policy, London School of Hygiene and Tropical Medicine (LSHTM), London, United Kingdom
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