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Taty N, Bompangue D, Moore S, Muyembe JJ, de Richemond NM. Spatiotemporal dynamics of cholera hotspots in the Democratic Republic of the Congo from 1973 to 2022. BMC Infect Dis 2024; 24:360. [PMID: 38549076 PMCID: PMC10976723 DOI: 10.1186/s12879-024-09164-9] [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: 10/03/2023] [Accepted: 02/22/2024] [Indexed: 04/01/2024] Open
Abstract
BACKGROUND Since the early 1970s, cholera outbreaks have been a major public health burden in the Democratic Republic of Congo (DRC). Cholera cases have been reported in a quasi-continuous manner in certain lakeside areas in the Great Lakes Region. As these cholera-endemic health zones constitute a starting point for outbreaks and diffusion towards other at-risk areas, they play a major role in cholera dynamics in the country. Monitoring the spatiotemporal dynamics of cholera hotspots and adjusting interventions accordingly thus reduces the disease burden in an efficient and cost-effective manner. METHODS A literature review was conducted to describe the spatiotemporal dynamics of cholera in the DRC at the province level from 1973 to 1999. We then identified and classified cholera hotspots at the provincial and health zone levels from 2003 to 2022 and described the spatiotemporal evolution of hotspots. We also applied and compared three different classification methods to ensure that cholera hotspots are identified and classified according to the DRC context. RESULTS According to all three methods, high-priority hotspots were concentrated in the eastern Great Lakes Region. Overall, hotspots largely remained unchanged over the course of the study period, although slight improvements were observed in some eastern hotspots, while other non-endemic areas in the west experienced an increase in cholera outbreaks. The Global Task Force on Cholera Control (GTFCC) and the Department of Ecology and Infectious Disease Control (DEIDC) methods largely yielded similar results for the high-risk hotspots. However, the medium-priority hotspots identified by the GTFCC method were further sub-classified by the DEIDC method, thereby providing a more detailed ranking for priority targeting. CONCLUSIONS Overall, the findings of this comprehensive study shed light on the dynamics of cholera hotspots in the DRC from 1973 to 2022. These results may serve as an evidence-based foundation for public health officials and policymakers to improve the implementation of the Multisectoral Cholera Elimination Plan, guiding targeted interventions and resource allocation to mitigate the impact of cholera in vulnerable communities.
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Affiliation(s)
- Nadège Taty
- Department of Infectious Disease Ecology and Control, Faculty of Medicine, University of Kinshasa, Kinshasa, Democratic Republic of the Congo.
- Montpellier Geography and Spatial Planning Laboratory, Paul Valéry Montpellier 3 University, Montpellier, France.
- National Program for the Elimination of Cholera and the Fight against Other Diarrheal Diseases, Ministry of Health, Hygiene and Prevention, Kinshasa, Democratic Republic of the Congo.
| | - Didier Bompangue
- Department of Infectious Disease Ecology and Control, Faculty of Medicine, University of Kinshasa, Kinshasa, Democratic Republic of the Congo
- National Program for the Elimination of Cholera and the Fight against Other Diarrheal Diseases, Ministry of Health, Hygiene and Prevention, Kinshasa, Democratic Republic of the Congo
- Chrono-Environment Laboratory, UMR 6249, University of Bourgogne Franche-Comté, Besançon, France
| | | | - J J Muyembe
- National Institute of Biomedical Research, Kinshasa, Democratic Republic of the Congo
| | - Nancy Meschinet de Richemond
- Montpellier Geography and Spatial Planning Laboratory, Paul Valéry Montpellier 3 University, Montpellier, France
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Bwire G, Sack DA, Lunkuse SM, Ongole F, Ngwa MC, Namanya DB, Nsungwa J, Aceng Ocero JR, Mwebesa HG, Muruta A, Nakinsige A, Kisakye A, Kalyebi P, Kemirembe J, Makumbi I, Kagirita A, Ampeire I, Mutegeki D, Matseketse D, Debes AK, Orach CG. Development of a Scorecard to Monitor Progress toward National Cholera Elimination: Its Application in Uganda. Am J Trop Med Hyg 2023; 108:954-962. [PMID: 37037429 PMCID: PMC10160876 DOI: 10.4269/ajtmh.23-0007] [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: 01/03/2023] [Accepted: 02/01/2023] [Indexed: 04/12/2023] Open
Abstract
In 2017, the Global Task Force for Cholera Control (GTFCC) set a goal to eliminate cholera from ≥ 20 countries and to reduce cholera deaths by 90% by 2030. Many countries have included oral cholera vaccine (OCV) in their cholera control plans. We felt that a simple, user-friendly monitoring tool would be useful to guide national progress toward cholera elimination. We reviewed cholera surveillance data of Uganda from 2015 to 2021 by date and district. We defined a district as having eliminated cholera if cholera was not reported in that district for at least 4 years. We prepared maps to show districts with cholera, districts that had eliminated it, and districts that had eliminated it but then "relapsed." These maps were compared with districts where OCV was used and the hotspot map recommended by the GTFCC. Between 2018 and 2021, OCV was administered in 16 districts previously identified as hotspots. In 2018, cholera was reported during at least one of the four previous years from 36 of the 146 districts of Uganda. This number decreased to 18 districts by 2021. Cholera was deemed "eliminated" from four of these 18 districts but then "relapsed." The cholera elimination scorecard effectively demonstrated national progress toward cholera elimination and identified districts where additional resources are needed to achieve elimination by 2030. Identification of the districts that have eliminated cholera and those that have relapsed will assist the national programs to focus on addressing the factors that result in elimination or relapse of cholera.
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Affiliation(s)
- Godfrey Bwire
- Department of Community Health, Ministry of Health Uganda, Kampala, Uganda
| | - David A. Sack
- Department of International Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland
| | - Stella M. Lunkuse
- Division of Surveillance, Knowledge and Information Management, Ministry of Health, Kampala, Uganda
| | - Francis Ongole
- Department of National Health Laboratory and Diagnostic Services, Ministry of Health, Kampala, Uganda
| | - Moise Chi Ngwa
- Department of International Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland
| | | | - Jesca Nsungwa
- Department of Maternal and Child Health, Ministry of Health, Kampala, Uganda
| | | | - Henry G. Mwebesa
- Office of the Director General Health Service, Ministry of Health, Kampala, Uganda
| | - Allan Muruta
- Department of Integrated Epidemiology and Public Health Emergencies, Ministry of Health, Kampala, Uganda
| | - Anne Nakinsige
- Division of Public Health Emergency Preparedness and Response, Ministry of Health, Kampala, Uganda
| | | | - Peter Kalyebi
- Department of Environmental Health, Ministry of Health, Kampala, Uganda
| | | | - Issa Makumbi
- Public Health Emergency Operation Centre, Ministry of Health, Kampala, Uganda
| | - Atek Kagirita
- Division of Surveillance, Knowledge and Information Management, Ministry of Health, Kampala, Uganda
| | - Immaculate Ampeire
- Uganda National Immunization Programme, Ministry of Health, Kampala, Uganda
| | - David Mutegeki
- Public Health Emergency Operation Centre, Ministry of Health, Kampala, Uganda
| | | | - Amanda Kay Debes
- Department of International Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland
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Kiama C, Okunga E, Muange A, Marwanga D, Langat D, Kuria F, Amoth P, Were I, Gachohi J, Ganda N, Martinez Valiente M, Njenga MK, Osoro E, Brunkard J. Mapping of cholera hotspots in Kenya using epidemiologic and water, sanitation, and hygiene (WASH) indicators as part of Kenya's new 2022-2030 cholera elimination plan. PLoS Negl Trop Dis 2023; 17:e0011166. [PMID: 36930650 PMCID: PMC10058159 DOI: 10.1371/journal.pntd.0011166] [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: 11/15/2022] [Revised: 03/29/2023] [Accepted: 02/13/2023] [Indexed: 03/18/2023] Open
Abstract
Cholera is an issue of major public health importance. It was first reported in Kenya in 1971, with the country experiencing outbreaks through the years, most recently in 2021. Factors associated with the outbreaks in Kenya include open defecation, population growth with inadequate expansion of safe drinking water and sanitation infrastructure, population movement from neighboring countries, crowded settings such as refugee camps coupled with massive displacement of persons, mass gathering events, and changes in rainfall patterns. The Ministry of Health, together with other ministries and partners, revised the national cholera control plan to a multisectoral cholera elimination plan that is aligned with the Global Roadmap for Ending Cholera. One of the key features in the revised plan is the identification of hotspots. The hotspot identification exercise followed guidance and tools provided by the Global Task Force on Cholera Control (GTFCC). Two epidemiological indicators were used to identify the sub-counties with the highest cholera burden: incidence per population and persistence. Additionally, two indicators were used to identify sub-counties with poor WASH coverage due to low proportions of households accessing improved water sources and improved sanitation facilities. The country reported over 25,000 cholera cases between 2015 and 2019. Of 290 sub-counties, 25 (8.6%) sub-counties were identified as a high epidemiological priority; 78 (26.9%) sub-counties were identified as high WASH priority; and 30 (10.3%) sub-counties were considered high priority based on a combination of epidemiological and WASH indicators. About 10% of the Kenyan population (4.89 million) is living in these 30-combination high-priority sub-counties. The novel method used to identify cholera hotspots in Kenya provides useful information to better target interventions in smaller geographical areas given resource constraints. Kenya plans to deploy oral cholera vaccines in addition to WASH interventions to the populations living in cholera hotspots as it targets cholera elimination by 2030.
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Affiliation(s)
- Catherine Kiama
- Washington State University, Global Health Kenya, Nairobi, Kenya
- * E-mail:
| | | | | | - Doris Marwanga
- Washington State University, Global Health Kenya, Nairobi, Kenya
| | | | | | | | - Ian Were
- Kenya Ministry of Health, Nairobi, Kenya
| | - John Gachohi
- Washington State University, Global Health Kenya, Nairobi, Kenya
- School of Public Health, Jomo Kenyatta University of Agriculture and Technology, Nairobi, Kenya
| | | | | | - M. Kariuki Njenga
- Washington State University, Global Health Kenya, Nairobi, Kenya
- Paul G. Allen School for Global Health, Washington State University, Pullman, Washington, United States of America
| | - Eric Osoro
- Washington State University, Global Health Kenya, Nairobi, Kenya
- Paul G. Allen School for Global Health, Washington State University, Pullman, Washington, United States of America
| | - Joan Brunkard
- Centers for Disease Control and Prevention, Atlanta, Georgia, United States of America
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Nazia N, Law J, Butt ZA. Modelling the spatiotemporal spread of COVID-19 outbreaks and prioritization of the risk areas in Toronto, Canada. Health Place 2023; 80:102988. [PMID: 36791508 PMCID: PMC9922578 DOI: 10.1016/j.healthplace.2023.102988] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/28/2022] [Revised: 12/16/2022] [Accepted: 02/09/2023] [Indexed: 02/16/2023]
Abstract
Modelling the spatiotemporal spread of a highly transmissible disease is challenging. We developed a novel spatiotemporal spread model, and the neighbourhood-level data of COVID-19 in Toronto was fitted into the model to visualize the spread of the disease in the study area within two weeks of the onset of first outbreaks from index neighbourhood to its first-order neighbourhoods (called dispersed neighbourhoods). We also model the data to classify hotspots based on the overall incidence rate and persistence of the cases during the study period. The spatiotemporal spread model shows that the disease spread to 1-4 neighbourhoods bordering the index neighbourhood within two weeks. Some dispersed neighbourhoods became index neighbourhoods and further spread the disease to their nearby neighbourhoods. Most of the sources of infection in the dispersed neighbourhood were households and communities (49%), and after excluding the healthcare institutions (40%), it becomes 82%, suggesting the expansion of transmission was from close contacts. The classification of hotspots informs high-priority areas concentrated in the northwestern and northeastern parts of Toronto. The spatiotemporal spread model along with the hotspot classification approach, could be useful for a deeper understanding of spatiotemporal dynamics of infectious diseases and planning for an effective mitigation strategy where local-level spatially enabled data are available.
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Affiliation(s)
- Nushrat Nazia
- School of Public Health Sciences, University of Waterloo, 200 University Ave W., Waterloo, ON, N2L3G1, Canada.
| | - Jane Law
- School of Public Health Sciences, University of Waterloo, 200 University Ave W., Waterloo, ON, N2L3G1, Canada; School of Planning, University of Waterloo, 200 University Ave W., Waterloo, ON, N2L3G1, Canada.
| | - Zahid Ahmad Butt
- School of Public Health Sciences, University of Waterloo, 200 University Ave W., Waterloo, ON, N2L3G1, Canada.
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Hounmanou YMG, Njamkepo E, Rauzier J, Gallandat K, Jeandron A, Kamwiziku G, Porten K, Luquero F, Abedi AA, Rumedeka BB, Miwanda B, Michael M, Okitayemba PW, Saidi JM, Piarroux R, Weill FX, Dalsgaard A, Quilici ML. Genomic Microevolution of Vibrio cholerae O1, Lake Tanganyika Basin, Africa. Emerg Infect Dis 2023; 29:149-153. [PMID: 36573719 PMCID: PMC9796204 DOI: 10.3201/eid2901.220641] [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] [Indexed: 12/29/2022] Open
Abstract
Africa's Lake Tanganyika basin is a cholera hotspot. During 2001-2020, Vibrio cholerae O1 isolates obtained from the Democratic Republic of the Congo side of the lake belonged to 2 of the 5 clades of the AFR10 sublineage. One clade became predominant after acquiring a parC mutation that decreased susceptibility to ciprofloxacin.
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Ateudjieu J, Sack DA, Nafack SS, Xiao S, Tchio-Nighie KH, Tchokomeni H, Bita’a LB, Nyibio PN, Guenou E, Mondung KM, Dieumo FFK, Ngome RM, Murt KN, Ram M, Ali M, Debes AK. An Age-stratified, Randomized Immunogenicity Trial of Killed Oral Cholera Vaccine with Delayed Second Dose in Cameroon. Am J Trop Med Hyg 2022; 107:974-983. [PMID: 36395746 PMCID: PMC9709001 DOI: 10.4269/ajtmh.22-0462] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2022] [Accepted: 08/20/2022] [Indexed: 11/01/2023] Open
Abstract
The recommended schedule for killed oral cholera vaccine (OCV) is two doses, 2 weeks apart. However, during vaccine campaigns, the second round is often delayed by several months. Because more information is needed to document antibody responses when the second dose is delayed, we conducted an open-label, phase 2, noninferiority clinical trial of OCV. One hundred eighty-six participants were randomized into three dose-interval groups (DIGs) to receive the second dose 2 weeks, 6 months, or 11.5 months after the first dose. The DIGs were stratified into three age strata: 1 to 4, 5 to 14, and > 14 years. Inaba and Ogawa vibriocidal titers were assessed before and after vaccination. The primary analysis was geometric mean titer (GMT) 2 weeks after the second dose. Data for primary analysis was available from 147 participants (54, 44, and 49 participants from the three DIGs respectively). Relative to the 2-week interval, groups receiving a delayed second dose had significantly higher GMTs after the second dose. Two weeks after the second dose, Inaba GMTs were 55.1 190.3, and 289.8 and Ogawa GMTs were 70.4, 134.5, and 302.4 for the three DIGs respectively. The elevated titers were brief, returning to lower levels within 3 months. We conclude that when the second dose of killed oral cholera vaccine was given after 6 or 11.5 months, vibriocidal titers were higher than when given after the standard period of 2 weeks. This provides reassurance that a delayed second dose does not compromise, but rather enhances, the serological response to the vaccine.
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Affiliation(s)
- Jérôme Ateudjieu
- MA Sante, Yaoundé, Cameroon
- Department of Public Health, Faculty of Medicine and Pharmaceutical Sciences, University of Dschang, Cameroon
- Clinical Research Unit, Division of Health Operations Research, Ministry of Public Health, Cameroon
| | - David A Sack
- Department of International Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland
| | | | - Shaoming Xiao
- Department of International Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland
| | | | | | | | | | | | | | | | - Rosanne Minone Ngome
- Department of Bacteriology-Parasitology-Mycology Laboratory, Centre Pasteur of Cameroon (CPC), Yaoundé, Cameroon
| | - Kelsey N. Murt
- Department of International Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland
| | - Malathi Ram
- Department of International Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland
| | - Mohammad Ali
- Department of International Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland
| | - Amanda K. Debes
- Department of International Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland
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Sack DA, Debes AK, Ateudjieu J, Bwire G, Ali M, Ngwa MC, Mwaba J, Chilengi R, Orach CC, Boru W, Mohamed AA, Ram M, George CM, Stine OC. Contrasting Epidemiology of Cholera in Bangladesh and Africa. J Infect Dis 2021; 224:S701-S709. [PMID: 34549788 PMCID: PMC8687066 DOI: 10.1093/infdis/jiab440] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022] Open
Abstract
In Bangladesh and West Bengal cholera is seasonal, transmission occurs consistently annually. By contrast, in most African countries, cholera has inconsistent seasonal patterns and long periods without obvious transmission. Transmission patterns in Africa occur during intermittent outbreaks followed by elimination of that genetic lineage. Later another outbreak may occur because of reintroduction of new or evolved lineages from adjacent areas, often by human travelers. These then subsequently undergo subsequent elimination. The frequent elimination and reintroduction has several implications when planning for cholera's elimination including: a) reconsidering concepts of definition of elimination, b) stress on rapid detection and response to outbreaks, c) more effective use of oral cholera vaccine and WASH, d) need to readjust estimates of disease burden for Africa, e) re-examination of water as a reservoir for maintaining endemicity in Africa. This paper reviews major features of cholera's epidemiology in African countries which appear different from the Ganges Delta.
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Affiliation(s)
- David A Sack
- Department of International Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA
| | - Amanda K Debes
- Department of International Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA
| | - Jerome Ateudjieu
- Meilleur Acces aux Soins de Sante, and Department of Public Health, Faculty of Medicine and Pharmaceutical Sciences, University of Dschang, and Clinical Research Unit, Division of Health Operations Research, Cameroon Ministry of Public Health, Yaoundé, Cameroon
| | - Godfrey Bwire
- Department of Integrated Epidemiology, Surveillance, and Public Health Emergencies, Ministry of Health, Kampala, Uganda
| | - Mohammad Ali
- Department of International Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA
| | - Moise Chi Ngwa
- Department of International Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA
| | - John Mwaba
- Centre for Infectious Disease Research in Zambia, Lusaka, Zambia
| | - Roma Chilengi
- Centre for Infectious Disease Research in Zambia, Lusaka, Zambia
| | - Christopher C Orach
- Department of Community Health and Behavioural Sciences, Makerere University School of Public Health, Kampala, Uganda
| | - Waqo Boru
- Ministry of Health and Field Epidemiology and Laboratory Training Program, Nairobi, Kenya
| | - Ahmed Abade Mohamed
- Tanzania Field Epidemiology and Laboratory Training Program, Dar-es-Salaam, Tanzania
| | - Malathi Ram
- Department of International Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA
| | - Christine Marie George
- Department of International Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA
| | - O Colin Stine
- Department of Epidemiology and Public Health, School of Medicine, University of Maryland, Baltimore, Maryland, USA
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