{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,18]],"date-time":"2026-03-18T23:15:55Z","timestamp":1773875755986,"version":"3.50.1"},"reference-count":66,"publisher":"American Medical Association (AMA)","issue":"3","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["JAMA Netw Open"],"abstract":"\n Importance<\/jats:title>\n Chikungunya virus has reemerged in some French overseas territories and mainland France, raising concern for its reintroduction in French Polynesia.<\/jats:p>\n <\/jats:sec>\n \n Objective<\/jats:title>\n To assess current population immunity to chikungunya virus and estimate future outbreak risk.<\/jats:p>\n <\/jats:sec>\n \n Design, Setting, and Participants<\/jats:title>\n This cross-sectional study included data from 2 serosurveys and used a modeling approach that integrated seroprevalence, contact matrices, and demographic characteristics. The first serosurvey was conducted on the island of Tahiti (June 2018) among schoolchildren aged 6 to 16 years. The second serosurvey (November 2019 to December 2021) included adults aged 18 to 69 years across French Polynesia, a French overseas territory in the Southeast Pacific that comprises 75 inhabited islands grouped into 5 subdivisions with 279\u202f000 people according to the 2022 census. Data analysis was conducted from April to June 2025.<\/jats:p>\n <\/jats:sec>\n \n Main Outcomes and Measures<\/jats:title>\n \n Main outcomes were seroprevalence rates and factors associated with seropositivity; age-stratified infection proportions for the 2014 to 2015 outbreak, pre-outbreak the basic reproduction number (R\n 0<\/jats:sub>\n ), the effective reproduction number (R\n \n eff<\/jats:sub>\n <\/jats:italic>\n ) for 2025, and R\n \n eff<\/jats:sub>\n <\/jats:italic>\n projections were estimated.\n <\/jats:p>\n <\/jats:sec>\n \n Results<\/jats:title>\n \n Serological data were available for 2363 participants (457 schoolchildren; median [IQR] age, 11 [8-13] years; 244 [53.3%] female, and 1906 adults; 38 [28-52] years; 1003 [52.6%] female). Seroprevalence was 62.8% (95% CI, 58.0%-67.0%) in schoolchildren, and the weighted seroprevalence was 67.6% (95% CI, 64.8%-70.3%) in adults. In adults, lower odds of seropositivity were associated with male sex (adjusted odds ratio [aOR], 0.71; 95% CI, 0.55-0.92), age groups 30 to 44 years and 45 to 69 years compared with 18 to 29 years (ages 30-44 years: aOR, 0.46; 95% CI, 0.32-0.66; ages 45-69 years: aOR, 0.33; 95% CI, 0.22-0.48), living in the Austral subdivision (aOR, 0.38; 95% CI, 0.27-0.55), and higher education (ie, university or more education: aOR, 0.51; 95% CI, 0.32-0.81). Living in larger households and being unpartnered were associated with higher odds of seropositivity (larger households: aOR, 1.69; 95% CI, 1.12-2.56; being unpartnered: aOR, 1.95; 95% CI, 1.03-3.69). Modeled infection rates for 2014 to 2015 ranged from 52.6% (95% credible interval [CrI], 43.6%-60.0%) in children aged 0 to 4 years to 80.8% (95% CrI, 73.3%-86.2%) in those aged 10 to 14 years. Inferred pre-outbreak R\n 0<\/jats:sub>\n was 1.78 (95% CrI, 1.73-1.82), and R\n \n eff<\/jats:sub>\n <\/jats:italic>\n for 2025 was estimated at 0.95 (95% CrI, 0.85-1.04). Assuming assortative mixing, projections suggest R\n \n eff<\/jats:sub>\n <\/jats:italic>\n would exceed 1 (lower 95% CrI &amp;gt;1) by 2028, but assuming random mixing, R\n \n eff<\/jats:sub>\n <\/jats:italic>\n would exceed 1 in 2051, more than 20 years later than the other estimate.\n <\/jats:p>\n <\/jats:sec>\n \n Conclusions and Relevance<\/jats:title>\n \n In this cross-sectional study, high chikungunya seroprevalence was observed, with heterogeneity between subdivisions, age groups, and other sociodemographic characteristics. Modeling analysis estimated R\n \n eff<\/jats:sub>\n <\/jats:italic>\n near 1 in 2025, suggesting sustained transmission could occur if chikungunya is reintroduced. These findings suggest that incorporating contact matrices could improve outbreak risk assessments, while assuming random mixing might underestimate reemergence timing.\n <\/jats:p>\n <\/jats:sec>","DOI":"10.1001\/jamanetworkopen.2026.2270","type":"journal-article","created":{"date-parts":[[2026,3,18]],"date-time":"2026-03-18T15:30:53Z","timestamp":1773847853000},"page":"e262270","source":"Crossref","is-referenced-by-count":0,"title":["Social Mixing Patterns and Chikungunya Reemergence Risk in French Polynesia"],"prefix":"10.1001","volume":"9","author":[{"given":"Kiyoji-ken","family":"Chung","sequence":"first","affiliation":[{"name":"Laboratory of Research on Emerging Viral Diseases, Institut Louis Malard\u00e9, Papeete, Tahiti, French Polynesia"},{"name":"Unit\u00e9 des virus \u00e9mergents, Aix-Marseille University, Universit\u00e0 di Corsica, IRD 190, Inserm 1207, Institut de Recherche Biom\u00e9dicale des Arm\u00e9es, Etablissement Fran\u00e7ais du Sang, Marseille, 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