{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,9]],"date-time":"2026-09-09T11:14:08Z","timestamp":1788952448787,"version":"build-2803163510"},"reference-count":14,"publisher":"MDPI AG","issue":"11","license":[{"start":{"date-parts":[[2025,11,6]],"date-time":"2025-11-06T00:00:00Z","timestamp":1762387200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100000805","name":"European Centre for Disease Prevention and Control","doi-asserted-by":"crossref","id":[{"id":"10.13039\/501100000805","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IJERPH"],"abstract":"<jats:p>During the 2022\u20132023 cholera outbreak in Lebanon, cases were reported through the District Health Information System 2 (DHIS2). We developed automated procedures in R computing language to improve completeness of routinely notified variables, apply case definition criteria, improve geographic accuracy and documentation of laboratory results. We developed R scripts for data cleaning, standardization, and reclassification, plotted epidemic curves and produced maps to display cholera incidence rates and rapid diagnostic test (RDT) coverage by district. We shared the R scripts on GitHub platform for open adaptation and use. Prior to cleaning, missingness reached 99.7% for inpatient status and 17\u201335% for other key variables. After cleaning, all fields were complete. Initially, 92.8% of cases were notified through DHIS2 as suspected and 7.2% as confirmed. Following reclassification, 40% were classified as suspected, 5.8% as confirmed, and 48.6% with unspecified classification. Laboratory data revealed that 5.8% of cases were culture positive, 2.2% RDT positive, and 65.1% had no documented testing. Among facility-entered cases (n = 5953), 11.4% were reported from a different governorate than the patient\u2019s residence. At the time of the outbreak, the daily maps were generated based on place of residence. Integrating R-based analytics with DHIS2 enhanced data completeness, improved case classification, and enabled more better spatial and laboratory analysis. This combined approach provided a clearer epidemiological picture of the cholera outbreak, supporting data-driven public health decision-making and highlighting the value of integrating analytical tools with routine surveillance systems.<\/jats:p>","DOI":"10.3390\/ijerph22111684","type":"journal-article","created":{"date-parts":[[2025,11,6]],"date-time":"2025-11-06T17:51:43Z","timestamp":1762451503000},"page":"1684","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Integrating DHIS2 and R for Enhanced Cholera Surveillance in Lebanon: A Case Study on Improving Data Quality"],"prefix":"10.3390","volume":"22","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-6649-3667","authenticated-orcid":false,"given":"Abass Toufic","family":"Jouny","sequence":"first","affiliation":[{"name":"Epidemiological Surveillance Program, Ministry of Public Health, Ras En Nabaa, Beirut 1107, Lebanon"},{"name":"Mediterranean and Black Sea Programme in Intervention Epidemiology Training (MediPIET), European Centre for Disease Prevention and Control (ECDC), 171 83 Stockholm, Sweden"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2148-7711","authenticated-orcid":false,"given":"Hawraa","family":"Sweidan","sequence":"additional","affiliation":[{"name":"Epidemiological Surveillance Program, Ministry of Public Health, Ras En Nabaa, Beirut 1107, Lebanon"},{"name":"Mediterranean and Black Sea Programme in Intervention Epidemiology Training (MediPIET), European Centre for Disease Prevention and Control (ECDC), 171 83 Stockholm, Sweden"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2943-5441","authenticated-orcid":false,"given":"Maryo","family":"Baakliny","sequence":"additional","affiliation":[{"name":"Epidemiological Surveillance Program, Ministry of Public Health, Ras En Nabaa, Beirut 1107, Lebanon"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Nada","family":"Ghosn","sequence":"additional","affiliation":[{"name":"Epidemiological Surveillance Program, Ministry of Public Health, Ras En Nabaa, Beirut 1107, Lebanon"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2025,11,6]]},"reference":[{"key":"ref_1","unstructured":"World Health Organization (2025, August 26). Cholera. Key Facts. Available online: https:\/\/www.who.int\/news-room\/fact-sheets\/detail\/cholera."},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Ali, M., Nelson, A.R., Lopez, A.L., and Sack, D.A. (2015). Updated global burden of cholera in endemic countries. PLoS Negl. Trop. Dis., 9.","DOI":"10.1371\/journal.pntd.0003832"},{"key":"ref_3","unstructured":"Global Task Force on Cholera Control (2025, August 26). Public Health Surveillance for Cholera\u2014Guidance Document 2024. Available online: https:\/\/www.gtfcc.org\/wp-content\/uploads\/2025\/04\/public-health-surveillance-for-cholera-guidance-document-2024.pdf."},{"key":"ref_4","unstructured":"Republic of Lebanon, Ministry of Public Health (2025, August 26). Cholera Outbreak Situation Reports 2022\u20132023. Beirut, Lebanon, Available online: https:\/\/www.moph.gov.lb\/ar\/Pages\/2\/64737\/cholera-in-lebanon."},{"key":"ref_5","unstructured":"District Health Information Software 2 (DHIS2) (2025, August 26). Health Information Management System. Available online: https:\/\/dhis2.org."},{"key":"ref_6","first-page":"38","article-title":"DHIS2: The tool to improve health data demand and use in Kenya","volume":"8","author":"Karuri","year":"2014","journal-title":"J. Health Inform. Dev. Ctries."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"698","DOI":"10.26719\/2024.30.10.698","article-title":"Retrospective analysis of a large-scale cholera outbreak in Sudan","volume":"30","author":"Haroun","year":"2024","journal-title":"East. Mediterr. Health J."},{"key":"ref_8","unstructured":"R Core Team (2023). R: A Language and Environment for Statistical Computing, R Foundation for Statistical Computing. Available online: https:\/\/www.r-project.org."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"439","DOI":"10.32614\/RJ-2018-009","article-title":"Simple Features for R: Standardized Support for Spatial Vector Data","volume":"10","author":"Pebesma","year":"2018","journal-title":"R J."},{"key":"ref_10","first-page":"529","article-title":"Migration from Epi Info to District Health Information Software 2 for Vaccine-Preventable Disease Surveillance\u2014WHO African Region, 2019\u20132023","volume":"73","author":"Adegoke","year":"2024","journal-title":"MMWR"},{"key":"ref_11","first-page":"45","article-title":"Critical analysis of infectious disease surveillance and response system in Nigeria","volume":"12","author":"Adewumi","year":"2025","journal-title":"Cost Effic. Health Res."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"62","DOI":"10.5334\/aogh.4742","article-title":"Integrating Surveillance and Climate Data for Cholera Early Warning in Ethiopia","volume":"91","author":"Dadi","year":"2025","journal-title":"Ann. Glob. Health"},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"6","DOI":"10.1186\/s13031-023-00504-1","article-title":"Usefulness of disease surveillance data in enhanced early warning of the cholera outbreak in Southwest Cameroon, 2018","volume":"17","author":"Kadia","year":"2023","journal-title":"Confl. Health"},{"key":"ref_14","doi-asserted-by":"crossref","unstructured":"Debes, A.K., Baumgartner, E.T., Williams, K.N., and Sack, D.A. (2025). A transformation in cholera surveillance. Lancet Infect Dis.","DOI":"10.1016\/S1473-3099(25)00408-6"}],"container-title":["International Journal of Environmental Research and Public Health"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1660-4601\/22\/11\/1684\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,11,8]],"date-time":"2025-11-08T05:14:24Z","timestamp":1762578864000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1660-4601\/22\/11\/1684"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,11,6]]},"references-count":14,"journal-issue":{"issue":"11","published-online":{"date-parts":[[2025,11]]}},"alternative-id":["ijerph22111684"],"URL":"https:\/\/doi.org\/10.3390\/ijerph22111684","relation":{},"ISSN":["1660-4601"],"issn-type":[{"value":"1660-4601","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,11,6]]}}}