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Kim BI, Achangwa C, Cho S, Ahn J, Won J, Do H, Lee D, Yoon B, Kim J, Ryu S. The Hand, Foot, and Mouth Disease Sentinel Surveillance System in South Korea: Retrospective Evaluation Study. JMIR Public Health Surveill 2024; 10:e59446. [PMID: 39045828 PMCID: PMC11287233 DOI: 10.2196/59446] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2024] [Revised: 06/10/2024] [Accepted: 06/13/2024] [Indexed: 07/25/2024] Open
Abstract
Background South Korea has implemented a hand, foot, and mouth disease (HFMD) surveillance system since 2009 to monitor incidence trends and identify disease burden. This nationwide surveillance involves a network of approximately 100 pediatric clinics that report all probable and confirmed HFMD cases. Following the COVID-19 pandemic, infectious disease surveillance systems must be evaluated to ensure the effective use of limited public health resources. Objective This study aimed to evaluate the HFMD sentinel surveillance system in South Korea from 2017 to 2022, focusing on the transition period after the COVID-19 pandemic. Methods We retrospectively reviewed the HFMD sentinel surveillance system from the Korea Disease Control and Prevention Agency using systematic guidelines for public health surveillance system evaluation developed by the US Centers for Disease Control and Prevention. We assessed the system's overall performance in 5 main factors: timeliness, stability, completeness, sensitivity, and representativeness (ie, the age and geographic distribution of sentinels). We rated these factors as weak, moderate, or good. Results Our study showed that the completeness, sensitivity, and age representativeness of the HFMD surveillance performance were temporarily reduced to moderate levels from 2020 to 2021 and recovered in 2022, while the timeliness and geographic representativeness were maintained at a good level throughout the study period. The stability of the surveillance was moderate from 2017 to 2021 and weak in 2022. Conclusions This is the first study to evaluate the HFMD surveillance system after the acute phase of the COVID-19 pandemic. We identified a temporarily reduced level of performance (ie, completeness, sensitivity, and age-specific representativeness) during the acute phase of the pandemic and good performance in 2022. Surveillance system evaluation and maintenance during public health emergencies will provide robust and reliable data to support public health policy development. Regular staff training programs and reducing staff turnover will improve HFMD surveillance system stability.
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Affiliation(s)
- Bryan Inho Kim
- Division of Infectious Disease Control, Korea Disease Control and Prevention Agency, Cheongju-si, Republic of Korea
| | - Chiara Achangwa
- Department of Preventive Medicine, College of Medicine, The Catholic University of Korea, R6117, Omibus Park, 222 Banpo-daero, Seocho-gu, Seoul, 06591, 82 0231478383, 82 025323820, Republic of Korea
| | - Seonghui Cho
- Department of Preventive Medicine, College of Medicine, The Catholic University of Korea, R6117, Omibus Park, 222 Banpo-daero, Seocho-gu, Seoul, 06591, 82 0231478383, 82 025323820, Republic of Korea
| | - Jisoo Ahn
- Department of Preventive Medicine, Konyang University College of Medicine, Daejeon, Republic of Korea
| | - Jisu Won
- Division of Infectious Disease Control, Korea Disease Control and Prevention Agency, Cheongju-si, Republic of Korea
| | - Hyunkyung Do
- Department of Preventive Medicine, Konyang University College of Medicine, Daejeon, Republic of Korea
| | - Dayeong Lee
- Department of Preventive Medicine, Konyang University College of Medicine, Daejeon, Republic of Korea
| | - Bohye Yoon
- Department of Preventive Medicine, Konyang University College of Medicine, Daejeon, Republic of Korea
| | - Joohee Kim
- Department of Preventive Medicine, Konyang University College of Medicine, Daejeon, Republic of Korea
| | - Sukhyun Ryu
- Department of Preventive Medicine, College of Medicine, The Catholic University of Korea, R6117, Omibus Park, 222 Banpo-daero, Seocho-gu, Seoul, 06591, 82 0231478383, 82 025323820, Republic of Korea
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Wanyana MW, King P, Migisha R, Kwesiga B, Okello PE, Kadobera D, Bulage L, Kayiwa J, Nankya AM, Ario AR, Harris JR. Evaluation of the sentinel yellow fever surveillance system in Uganda, 2017-2022: strengths and weaknesses. BMC Infect Dis 2024; 24:686. [PMID: 38982363 PMCID: PMC11234539 DOI: 10.1186/s12879-024-09580-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2023] [Accepted: 07/01/2024] [Indexed: 07/11/2024] Open
Abstract
BACKGROUND Uganda has a sentinel surveillance system in seven high-risk sites to monitor yellow fever (YF) patterns and detect outbreaks. We evaluated the performance of this system from 2017 to 2022. METHODS We evaluated selected attributes, including timeliness (lags between different critical time points), external completeness (proportion of expected sentinel sites reporting ≥ 1 suspect case in the system annually), and internal completeness (proportion of reports with the minimum required data elements filled), using secondary data in the YF surveillance database from January 2017-July 2022. We conducted key informant interviews with stakeholders at health facility and national level to assess usefulness, flexibility, simplicity, and acceptability of the surveillance system. RESULTS In total, 3,073 suspected and 15 confirmed YF cases were reported. The median time lag from sample collection to laboratory shipment was 37 days (IQR:21-54). External completeness was 76%; internal completeness was 65%. Stakeholders felt that the surveillance system was simple and acceptable, but were uncertain about flexibility. Most (71%) YF cases in previous outbreaks were detected through the sentinel surveillance system; data were used to inform interventions such as intensified YF vaccination. CONCLUSION The YF sentinel surveillance system was useful in detecting outbreaks and informing public health action. Delays in case confirmation and incomplete data compromised its overall effectiveness and efficiency.
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Affiliation(s)
- Mercy Wendy Wanyana
- Uganda Public Health Fellowship Program, Uganda National Institute of Public Health, Kampala, Uganda.
| | - Patrick King
- Uganda Public Health Fellowship Program, Uganda National Institute of Public Health, Kampala, Uganda
| | - Richard Migisha
- Uganda Public Health Fellowship Program, Uganda National Institute of Public Health, Kampala, Uganda
| | - Benon Kwesiga
- Uganda Public Health Fellowship Program, Uganda National Institute of Public Health, Kampala, Uganda
| | - Paul Edward Okello
- Uganda Public Health Fellowship Program, Uganda National Institute of Public Health, Kampala, Uganda
| | - Daniel Kadobera
- Uganda Public Health Fellowship Program, Uganda National Institute of Public Health, Kampala, Uganda
| | - Lilian Bulage
- Uganda Public Health Fellowship Program, Uganda National Institute of Public Health, Kampala, Uganda
| | - Joshua Kayiwa
- Ministry of Health, Uganda National Institute of Public Health, Kampala, Uganda
| | | | - Alex Riolexus Ario
- Ministry of Health, Uganda National Institute of Public Health, Kampala, Uganda
| | - Julie R Harris
- US Centers for Disease Control and Prevention, Kampala, Uganda
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Guillot C, Aenishaenslin C, Acheson ES, Koffi J, Bouchard C, Leighton PA. Spatial multi-criteria decision analysis for the selection of sentinel regions in tick-borne disease surveillance. BMC Public Health 2024; 24:294. [PMID: 38267914 PMCID: PMC10809750 DOI: 10.1186/s12889-024-17684-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2023] [Accepted: 01/05/2024] [Indexed: 01/26/2024] Open
Abstract
BACKGROUND The implementation of cost-effective surveillance systems is essential for tracking the emerging risk of tick-borne diseases. In Canada, where Lyme disease is a growing public health concern, a national sentinel surveillance network was designed to follow the epidemiological portrait of this tick-borne disease across the country. The surveillance network consists of sentinel regions, with active drag sampling carried out annually in all regions to assess the density of Ixodes spp. ticks and prevalence of various tick-borne pathogens in the tick population. The aim of the present study was to prioritize sentinel regions by integrating different spatial criteria relevant to the surveillance goals. METHODS We used spatially-explicit multi-criteria decision analyses (MCDA) to map priority areas for surveillance across Canada, and to evaluate different scenarios using sensitivity analyses. Results were shared with stakeholders to support their decision making for the selection of priority areas to survey during active surveillance activities. RESULTS Weights attributed to criteria by decision-makers were overall consistent. Sensitivity analyses showed that the population criterion had the most impact on rankings. Thirty-seven sentinel regions were identified across Canada using this systematic and transparent approach. CONCLUSION This novel application of spatial MCDA to surveillance network design favors inclusivity of nationwide partners. We propose that such an approach can support the standardized planning of spatial design of sentinel surveillance not only for vector-borne disease BDs, but more broadly for infectious disease surveillance where spatial design is an important component.
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Affiliation(s)
- C Guillot
- Groupe de recherche en épidémiologie des zoonoses et santé publique (GREZOSP), Department of Pathology and Microbiology, Faculty of Veterinary Medicine, University of Montreal, Montreal, Quebec, Canada.
- Faculty of Medicine and Health Sciences, University of Sherbrooke, Sherbrooke, Quebec, Canada.
- Centre de recherche en santé publique (CRESP) de l'Université de Montréal et du CIUSSS du Centre-Sud-de-l'Île-de-Montréal, University of Montreal, Montreal, Quebec, Canada.
| | - C Aenishaenslin
- Groupe de recherche en épidémiologie des zoonoses et santé publique (GREZOSP), Department of Pathology and Microbiology, Faculty of Veterinary Medicine, University of Montreal, Montreal, Quebec, Canada
- Centre de recherche en santé publique (CRESP) de l'Université de Montréal et du CIUSSS du Centre-Sud-de-l'Île-de-Montréal, University of Montreal, Montreal, Quebec, Canada
| | - E S Acheson
- Groupe de recherche en épidémiologie des zoonoses et santé publique (GREZOSP), Department of Pathology and Microbiology, Faculty of Veterinary Medicine, University of Montreal, Montreal, Quebec, Canada
- Public Health Risk Sciences Divisions, National Microbiology Laboratory, Public Health Agency of Canada, Saint-Hyacinthe, Quebec, Canada
| | - J Koffi
- Groupe de recherche en épidémiologie des zoonoses et santé publique (GREZOSP), Department of Pathology and Microbiology, Faculty of Veterinary Medicine, University of Montreal, Montreal, Quebec, Canada
- Policy Integration and Zoonoses Division, Centre for Food-borne, Environmental and Zoonotic Infectious Diseases, Public Health Agency of Canada, Saint-Hyacinthe, Quebec, Canada
| | - C Bouchard
- Groupe de recherche en épidémiologie des zoonoses et santé publique (GREZOSP), Department of Pathology and Microbiology, Faculty of Veterinary Medicine, University of Montreal, Montreal, Quebec, Canada
- Public Health Risk Sciences Divisions, National Microbiology Laboratory, Public Health Agency of Canada, Saint-Hyacinthe, Quebec, Canada
| | - P A Leighton
- Groupe de recherche en épidémiologie des zoonoses et santé publique (GREZOSP), Department of Pathology and Microbiology, Faculty of Veterinary Medicine, University of Montreal, Montreal, Quebec, Canada
- Centre de recherche en santé publique (CRESP) de l'Université de Montréal et du CIUSSS du Centre-Sud-de-l'Île-de-Montréal, University of Montreal, Montreal, Quebec, Canada
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Bowser N, Bouchard C, Sautié Castellanos M, Baron G, Carabin H, Chuard P, Leighton P, Milord F, Richard L, Savage J, Tardy O, Aenishaenslin C. Self-reported tick exposure as an indicator of Lyme disease risk in an endemic region of Quebec, Canada. Ticks Tick Borne Dis 2024; 15:102271. [PMID: 37866213 DOI: 10.1016/j.ttbdis.2023.102271] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2023] [Revised: 09/13/2023] [Accepted: 10/07/2023] [Indexed: 10/24/2023]
Abstract
BACKGROUND Lyme disease (LD) and other tick-borne diseases are emerging across Canada. Spatial and temporal LD risk is typically estimated using acarological surveillance and reported human cases, the former not considering human behavior leading to tick exposure and the latter occurring after infection. OBJECTIVES The primary objective was to explore, at the census subdivision level (CSD), the associations of self-reported tick exposure, alternative risk indicators (predicted tick density, eTick submissions, public health risk level), and ecological variables (Ixodes scapularis habitat suitability index and cumulative degree days > 0 °C) with incidence proportion of LD. A secondary objective was to explore which of these predictor variables were associated with self-reported tick exposure at the CSD level. METHODS Self-reported tick exposure was measured in a cross-sectional populational health survey conducted in 2018, among 10,790 respondents living in 116 CSDs of the Estrie region, Quebec, Canada. The number of reported LD cases per CSD in 2018 was obtained from the public health department. Generalized linear mixed-effets models accounting for spatial autocorrelation were built to fulfill the objectives. RESULTS Self-reported tick exposure ranged from 0.0 % to 61.5 % (median 8.9 %) and reported LD incidence rates ranged from 0 to 324 cases per 100,000 person-years, per CSD. A positive association was found between self-reported tick exposure and LD incidence proportion (ß = 0.08, CI = 0.04,0.11, p < 0.0001). The best-fit model included public health risk level (AIC: 144.2), followed by predicted tick density, ecological variables, self-reported tick exposure and eTick submissions (AIC: 158.4, 158.4, 160.4 and 170.1 respectively). Predicted tick density was the only significant predictor of self-reported tick exposure (ß = 0.83, CI = 0.16,1.50, p = 0.02). DISCUSSION This proof-of-concept study explores self-reported tick exposure as a potential indicator of LD risk using populational survey data. This approach may offer a low-cost and simple tool for evaluating LD risk and deserves further evaluation.
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Affiliation(s)
- Natasha Bowser
- Groupe de Recherche en Épidémiologie des Zoonoses et Santé Publique (GREZOSP), Faculté de Médecine Vétérinaire, Université de Montréal, Saint-Hyacinthe, Québec, Canada; Centre de Recherche en Santé Publique (CReSP) de l'Université de Montréal et du CIUSSS du Centre-Sud-de-l'Île-de-Montréal, Montréal, Québec, Canada; Département de Pathologie et de Microbiologie, Faculté de Médecine Vétérinaire, Université de Montréal, Canada.
| | - Catherine Bouchard
- Groupe de Recherche en Épidémiologie des Zoonoses et Santé Publique (GREZOSP), Faculté de Médecine Vétérinaire, Université de Montréal, Saint-Hyacinthe, Québec, Canada; Public Health Risk Sciences Division, National Microbiology Laboratory, Public Health Agency of Canada, Saint-Hyacinthe, Québec, Canada; Département de Pathologie et de Microbiologie, Faculté de Médecine Vétérinaire, Université de Montréal, Canada
| | | | - Geneviève Baron
- Direction de la Santé Publique, CIUSSS de l'Estrie-CHUS, Québec, Canada; Département Des Sciences de la Santé Communautaire, Faculté de Médecine et Des Sciences de la Santé, Université de Sherbrooke, Sherbrooke, Canada
| | - Hélène Carabin
- Groupe de Recherche en Épidémiologie des Zoonoses et Santé Publique (GREZOSP), Faculté de Médecine Vétérinaire, Université de Montréal, Saint-Hyacinthe, Québec, Canada; Centre de Recherche en Santé Publique (CReSP) de l'Université de Montréal et du CIUSSS du Centre-Sud-de-l'Île-de-Montréal, Montréal, Québec, Canada; Département de Pathologie et de Microbiologie, Faculté de Médecine Vétérinaire, Université de Montréal, Canada; Département de Médecine Sociale et Préventive, École de santé publique de l'Université de Montréal, Canada
| | - Pierre Chuard
- Department of Geography, Planning and Environment, Concordia University, Montreal, Canada
| | - Patrick Leighton
- Groupe de Recherche en Épidémiologie des Zoonoses et Santé Publique (GREZOSP), Faculté de Médecine Vétérinaire, Université de Montréal, Saint-Hyacinthe, Québec, Canada; Centre de Recherche en Santé Publique (CReSP) de l'Université de Montréal et du CIUSSS du Centre-Sud-de-l'Île-de-Montréal, Montréal, Québec, Canada; Département de Pathologie et de Microbiologie, Faculté de Médecine Vétérinaire, Université de Montréal, Canada
| | - François Milord
- Département Des Sciences de la Santé Communautaire, Faculté de Médecine et Des Sciences de la Santé, Université de Sherbrooke, Sherbrooke, Canada; Institut national de santé publique du Québec, Québec, Canada
| | - Lucie Richard
- Centre de Recherche en Santé Publique (CReSP) de l'Université de Montréal et du CIUSSS du Centre-Sud-de-l'Île-de-Montréal, Montréal, Québec, Canada; Faculté des Sciences Infirmières, Université de Montréal, Canada
| | - Jade Savage
- Department of Biology and Biochemistry, Bishop's University, Canada
| | - Olivia Tardy
- Groupe de Recherche en Épidémiologie des Zoonoses et Santé Publique (GREZOSP), Faculté de Médecine Vétérinaire, Université de Montréal, Saint-Hyacinthe, Québec, Canada; Public Health Risk Sciences Division, National Microbiology Laboratory, Public Health Agency of Canada, Saint-Hyacinthe, Québec, Canada
| | - Cécile Aenishaenslin
- Groupe de Recherche en Épidémiologie des Zoonoses et Santé Publique (GREZOSP), Faculté de Médecine Vétérinaire, Université de Montréal, Saint-Hyacinthe, Québec, Canada; Centre de Recherche en Santé Publique (CReSP) de l'Université de Montréal et du CIUSSS du Centre-Sud-de-l'Île-de-Montréal, Montréal, Québec, Canada; Département de Pathologie et de Microbiologie, Faculté de Médecine Vétérinaire, Université de Montréal, Canada
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Mayor A, Ishengoma DS, Proctor JL, Verity R. Sampling for malaria molecular surveillance. Trends Parasitol 2023; 39:954-968. [PMID: 37730525 PMCID: PMC10580323 DOI: 10.1016/j.pt.2023.08.007] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2023] [Revised: 08/22/2023] [Accepted: 08/23/2023] [Indexed: 09/22/2023]
Abstract
Strategic use of Plasmodium falciparum genetic variation has great potential to inform public health actions for malaria control and elimination. Malaria molecular surveillance (MMS) begins with a strategy to identify and collect parasite samples, guided by public-health priorities. In this review we discuss sampling design practices for MMS and point out epidemiological, biological, and statistical factors that need to be considered. We present examples for different use cases, including detecting emergence and spread of rare variants, establishing transmission sources and inferring changes in malaria transmission intensity. This review will potentially guide the collection of samples and data, serve as a starting point for further methodological innovation, and enhance utilization of MMS to support malaria elimination.
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Affiliation(s)
- Alfredo Mayor
- ISGlobal, Hospital Clínic - Universitat de Barcelona, Barcelona, Spain; Centro de Investigação em Saúde de Manhiça (CISM), Maputo, Mozambique; Department of Physiologic Sciences, Faculty of Medicine, Universidade Eduardo Mondlane, Maputo, Mozambique.
| | - Deus S Ishengoma
- National Institute for Medical Research (NIMR), Dar es Salaam, Tanzania; Faculty of Pharmaceutical Sciences, Monash University, Melbourne, VIC, Australia; Harvard T.H. Chan School of Public Health, Harvard University, Boston, MA, USA
| | - Joshua L Proctor
- Institute for Disease Modeling in Global Health, Bill and Melinda Gates Foundation, Seattle, WA, USA
| | - Robert Verity
- MRC Centre for Global Infectious Disease Analysis, Imperial College, London, UK
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