{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,15]],"date-time":"2026-09-15T10:20:26Z","timestamp":1789467626116,"version":"build-2803163510"},"reference-count":55,"publisher":"MDPI AG","issue":"9","license":[{"start":{"date-parts":[[2026,9,15]],"date-time":"2026-09-15T00:00:00Z","timestamp":1789430400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"French Agence Nationale de Recherche sur le SIDA"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Microorganisms"],"abstract":"<jats:p>Seroprevalence surveys constitute a critical tool for estimating population exposure to infectious agents, particularly during public health emergencies. In the context of the coronavirus disease 2019 (COVID-19) pandemic, such surveys revealed that the circulation of Severe Acute Respiratory Syndrome Coronavirus 2 in Africa had been largely underestimated. The validity of these surveys, however, depends not only on the reliability of diagnostic tests but also on operational conditions, which are frequently challenged by fear, misinformation, and logistical constraints. In the Democratic Republic of the Congo, the National Institute of Biomedical Research conducted two seroprevalence surveys in Kinshasa in 2020 on behalf the project \u201cAppui \u00e0 la Riposte Africaine \u00e0 l\u2019Epid\u00e9mie de COVID-19\u201d (ARIACOV). This study described the challenges encountered and the adaptive strategies employed during these surveys, in order to improve future investigations. The study population comprised 41 eligible field workers who participated in the 2020 ARIACOV seroprevalence surveys in Kinshasa, including 28 interviewers and 13 specimen collectors. Of these, 24 individuals (16 interviewers and 8 specimen collectors) initially confirmed their participation. Ultimately, 15 participants took part in the focus group discussions, comprising 11 interviewers (39.3% of the 28 eligible interviewers) and 4 specimen collectors (30.8% of the 13 eligible specimen collectors). We collected data through two focus groups held in a single session, using a pre-tested semi-structured guide. Discussions were audio-recorded and complemented by observational notes until empirical saturation was achieved. We applied deductive thematic analysis, following Braun and Clarke\u2019s framework, to three predefined domains: transportation, survey procedures, and sample management. The application of systematic manual coding, combined with researcher triangulation, reinforced the rigor and enhanced the credibility of the findings. The findings highlighted community mistrust, driven by rumors, apprehension regarding blood collection, financial suspicions, and inadequate communication. In addition, logistical and transportation challenges significantly constrained survey feasibility. Nonetheless, a range of adaptive strategies were implemented, enabling the successful conduct of the surveys despite the pandemic context and limited resources. The participants\u2019 narratives suggest that strengthening field workers\u2019 training, improving transparency, and working alongside community health workers could contribute to enhance the effectiveness of serological surveys during health crises in resource-constrained environments.<\/jats:p>","DOI":"10.3390\/microorganisms14092056","type":"journal-article","created":{"date-parts":[[2026,9,15]],"date-time":"2026-09-15T08:16:48Z","timestamp":1789460208000},"page":"2056","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Challenges and Adaptations in COVID-19 Seroprevalence Surveys: Insights from Kinshasa, the Democratic Republic of the Congo"],"prefix":"10.3390","volume":"14","author":[{"given":"Benoit","family":"Mputu-Ngoyi","sequence":"first","affiliation":[{"name":"D\u00e9partement de Biologie M\u00e9dicale, Cliniques Universitaires de Kinshasa, Kinshasa P.O. Box 127, Democratic Republic of the Congo"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0000-1843-9634","authenticated-orcid":false,"given":"Angele","family":"Dilu-Keti","sequence":"additional","affiliation":[{"name":"TransVIHMI, Universit\u00e9 de Montpellier, Institut de Recherche pour le D\u00e9veloppement (IRD), Institut National de Sant\u00e9 et de Recherche M\u00e9dicale (INSERM), 911 Avenue Agropolis, BP 64501, 34394 Montpellier CEDEX 5, France"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Paul","family":"Tshiminyi-Munkamba","sequence":"additional","affiliation":[{"name":"D\u00e9partement de Virologie, Institut National de Recherche Biom\u00e9dicale, Kinshasa 01204, Democratic Republic of the Congo"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Marc K.","family":"Yambayamba","sequence":"additional","affiliation":[{"name":"D\u00e9partement d\u2019Epid\u00e9miologie et Biostatistiques, Ecole de Sant\u00e9 Publique, Universit\u00e9 de Kinshasa, Kinshasa P.O. Box 127, Democratic Republic of the Congo"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8303-318X","authenticated-orcid":false,"given":"Yannick","family":"Munyeku-Bazitama","sequence":"additional","affiliation":[{"name":"D\u00e9partement de Virologie, Institut National de Recherche Biom\u00e9dicale, Kinshasa 01204, Democratic Republic of the Congo"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4261-4399","authenticated-orcid":false,"given":"Sheila","family":"Makiala-Mandanda","sequence":"additional","affiliation":[{"name":"D\u00e9partement de Biologie M\u00e9dicale, Cliniques Universitaires de Kinshasa, Kinshasa P.O. Box 127, Democratic Republic of the Congo"},{"name":"D\u00e9partement de Virologie, Institut National de Recherche Biom\u00e9dicale, Kinshasa 01204, Democratic Republic of the Congo"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2850-7498","authenticated-orcid":false,"given":"Antoine","family":"Nkuba-Ndaye","sequence":"additional","affiliation":[{"name":"D\u00e9partement de Biologie M\u00e9dicale, Cliniques Universitaires de Kinshasa, Kinshasa P.O. Box 127, Democratic Republic of the Congo"},{"name":"TransVIHMI, Universit\u00e9 de Montpellier, Institut de Recherche pour le D\u00e9veloppement (IRD), Institut National de Sant\u00e9 et de Recherche M\u00e9dicale (INSERM), 911 Avenue Agropolis, BP 64501, 34394 Montpellier CEDEX 5, France"},{"name":"D\u00e9partement de Virologie, Institut National de Recherche Biom\u00e9dicale, Kinshasa 01204, Democratic Republic of the Congo"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Steve","family":"Ahuka-Mundeke","sequence":"additional","affiliation":[{"name":"D\u00e9partement de Biologie M\u00e9dicale, Cliniques Universitaires de Kinshasa, Kinshasa P.O. Box 127, Democratic Republic of the Congo"},{"name":"D\u00e9partement de Virologie, Institut National de Recherche Biom\u00e9dicale, Kinshasa 01204, Democratic Republic of the Congo"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2026,9,15]]},"reference":[{"key":"ref_1","unstructured":"World Health Organization (2017). Global Hepatitis Report 2017, WHO. Available online: https:\/\/apps.who.int\/iris\/handle\/10665\/255016."},{"key":"ref_2","unstructured":"World Health Organization (2015). Rubella Surveillance: Guidelines for Standardization of Data Collection, Analysis and Reporting, WHO. Available online: https:\/\/www.who.int\/publications\/i\/item\/9789241549370."},{"key":"ref_3","unstructured":"World Health Organization, Regional Office for Africa (2016). Atlas des Statistiques Sanitaires Africaines 2016, WHO\/AFRO. 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