Towards elimination of chronic viral hepatitis in French Polynesia: results from a national population-based survey.

Background: In French Polynesia, hepatitis B virus (HBV) infection appears as a major risk factor for hepatocellular carcinoma (HCC), which detection rate in the Austral archipelago is among the highest in the world. Through a nationally representative cross-sectional survey of the adult population, this study aimed at assessing the prevalence of HBV, but also hepatitis C virus (HCV), and hepatitis delta virus (HDV). Methods: A total of 1942 blood samples from participants aged 18-69 years were tested for anti-HBc, anti-HBs, HBsAg, anti-HCV IgG, and HDV RNA. Complete genome sequencing of detected HBV strains was performed. Findings: Among participants, 315/1834, 582/1834, 33/1834, 0/1857, and 0/33 tested positive for anti-HBc, anti-HBs, HBsAg, anti-HCV IgG, and HDV RNA, respectively. The population prevalence of HBsAg was estimated at 1.0% (95% CI: 0.6-1.7). All HBsAg carriers were born in French Polynesia before vaccination at birth became mandatory. In multivariate analyses, identified factors associated with HBsAg carriage included: the archipelago of residence (p < 0.0001), age (p < 0.0001), and education level (p = 0.0077). HBV genotypes B, C, and F were detected. Interpretation: French Polynesia has a low endemicity level of HBV and its population may be considered at low risk for HCV and HDV infection. However, prevalence of HBsAg was found concerning in Austral (3.8%; 95% CI: 1.9-7.5) and Marquesas (6.5%; 95% CI: 3.8-11) archipelagoes. In the Austral archipelago, the presence of genotype C may account for the elevated rate of HCC. Our findings warrant more efforts to improve access to detection, prevention and care to people born before the systematic vaccination policy application, and residing in higher-risk areas, to achieve HBV elimination in French Polynesia. Funding: Research Delegation of French Polynesia.

Real-time surveillance of international SARS-CoV-2 prevalence using systematic traveller arrival screening: An observational study.

BACKGROUND: Effective Coronavirus Disease 2019 (COVID-19) response relies on good knowledge of population infection dynamics, but owing to under-ascertainment and delays in symptom-based reporting, obtaining reliable infection data has typically required large dedicated local population studies. Although many countries implemented Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) testing among travellers, it remains unclear how accurately arrival testing data can capture international patterns of infection, because those arrival testing data were rarely reported systematically, and predeparture testing was often in place as well, leading to nonrepresentative infection status among arrivals. METHODS AND FINDINGS: In French Polynesia, testing data were reported systematically with enforced predeparture testing type and timing, making it possible to adjust for nonrepresentative infection status among arrivals. Combining statistical models of polymerase chain reaction (PCR) positivity with data on international travel protocols, we reconstructed estimates of prevalence at departure using only testing data from arrivals. We then applied this estimation approach to the United States of America and France, using data from over 220,000 tests from travellers arriving into French Polynesia between July 2020 and March 2022. We estimated a peak infection prevalence at departure of 2.1% (95% credible interval: 1.7, 2.6%) in France and 1% (95% CrI: 0.63, 1.4%) in the USA in late 2020/early 2021, with prevalence of 4.6% (95% CrI: 3.9, 5.2%) and 4.3% (95% CrI: 3.6, 5%), respectively, estimated for the Omicron BA.1 waves in early 2022. We found that our infection estimates were a leading indicator of later reported case dynamics, as well as being consistent with subsequent observed changes in seroprevalence over time. We did not have linked data on traveller demography or unbiased domestic infection estimates (e.g., from random community infection surveys) in the USA and France. However, our methodology would allow for the incorporation of prior data from additional sources if available in future. CONCLUSIONS: As well as elucidating previously unmeasured infection dynamics in these countries, our analysis provides a proof-of-concept for scalable and accurate leading indicator of global infections during future pandemics.

Unravelling the determinants of human health in French Polynesia: the MATAEA project.

Background: French Polynesia is a French overseas collectivity in the Southeast Pacific, comprising 75 inhabited islands across five archipelagoes. The human settlement of the region corresponds to the last massive migration of humans to empty territories, but its timeline is still debated. Despite their recent population history and geographical isolation, inhabitants of French Polynesia experience health issues similar to those of continental countries. Modern lifestyles and increased longevity have led to a rise in non-communicable diseases (NCDs) such as obesity, diabetes, hypertension, and cardiovascular diseases. Likewise, international trade and people mobility have caused the emergence of communicable diseases (CDs) including mosquito-borne and respiratory diseases. Additionally, chronic pathologies including acute rheumatic fever, liver diseases, and ciguatera, are highly prevalent in French Polynesia. However, data on such diseases are scarce and not representative of the geographic fragmentation of the population. Objectives: The present project aims to estimate the prevalence of several NCDs and CDs in the population of the five archipelagoes, and identify associated risk factors. Moreover, genetic analyses will contribute to determine the sequence and timings of the peopling history of French Polynesia, and identify causal links between past genetic adaptation to island environments, and present-day susceptibility to certain diseases. Methods: This cross-sectional survey is based on the random selection of 2,100 adults aged 18-69 years and residing on 18 islands from the five archipelagoes. Each participant answered a questionnaire on a wide range of topics (including demographic characteristics, lifestyle habits and medical history), underwent physical measurements (height, weight, waist circumference, arterial pressure, and skin pigmentation), and provided biological samples (blood, saliva, and stool) for biological, genetic and microbiological analyses. Conclusion: For the first time in French Polynesia, the present project allows to collect a wide range of data to explore the existence of indicators and/or risk factors for multiple pathologies of public health concern. The results will help health authorities to adapt actions and preventive measures aimed at reducing the incidence of NCDs and CDs. Moreover, the new genomic data generated in this study, combined with anthropological data, will increase our understanding of the peopling history of French Polynesia. Clinical trial registration: https://clinicaltrials.gov/, identifier: NCT06133400.

Self-collection and pooling of samples as resources-saving strategies for RT-PCR-based SARS-CoV-2 surveillance, the example of travelers in French Polynesia.

In French Polynesia, the first case of SARS-CoV-2 infection was detected on March 10th, 2020, in a resident returning from France. Between March 28th and July 14th, international air traffic was interrupted and local transmission of SARS-CoV-2 was brought under control, with only 62 cases recorded. The main challenge for reopening the air border without requiring travelers to quarantine on arrival was to limit the risk of re-introducing SARS-CoV-2. Specific measures were implemented, including the obligation for all travelers to have a negative RT-PCR test for SARS-CoV-2 carried out within 3 days before departure, and to perform another RT-PCR testing 4 days after arrival. Because of limitation in available medical staff, travelers were provided a kit allowing self-collection of oral and nasal swabs. In addition to increase our testing capacity, self-collected samples from up to 10 travelers were pooled before RNA extraction and RT-PCR testing. When a pool tested positive, RNA extraction and RT-PCR were performed on each individual sample. We report here the results of COVID-19 surveillance (COV-CHECK PORINETIA) conducted between July 15th, 2020, and February 15th, 2021, in travelers using self-collection and pooling approaches. We tested 5,982 pools comprising 59,490 individual samples, and detected 273 (0.46%) travelers positive for SARS-CoV-2. A mean difference of 1.17 Ct (CI 95% 0.93-1.41) was found between positive individual samples and pools (N = 50), probably related to the volume of samples used for RNA extraction (200 µL versus 50 µL, respectively). Retrospective testing of positive samples self-collected from October 20th, 2020, using variants-specific amplification kit and spike gene sequencing, found at least 6 residents infected by the Alpha variant. Self-collection and pooling approaches allowed large-scale screening for SARS-CoV-2 using less human, material and financial resources. Moreover, this strategy allowed detecting the introduction of SARS-CoV-2 variants of concern in French Polynesia.

Screening for Predictors of Chronic Ciguatera Poisoning: An Exploratory Analysis among Hospitalized Cases from French Polynesia.

Ciguatera poisoning is a globally occurring seafood disease caused by the ingestion of marine products contaminated with dinoflagellate produced neurotoxins. Persistent forms of ciguatera, which prove to be highly debilitating, are poorly studied and represent a significant medical issue. The present study aims to better understand chronic ciguatera manifestations and identify potential predictive factors for their duration. Medical files of 49 patients were analyzed, and the post-hospitalization evolution of the disease assessed through a follow-up questionnaire. A rigorous logistic lasso regression model was applied to select significant predictors from a list of 37 patient characteristics potentially predictive of having chronic symptoms. Missing data were handled by complete case analysis, and a survival analysis was implemented. All models used standardized variables, and multiple comparisons in the survival analyses were handled by Bonferroni correction. Among all studied variables, five significant predictors of having symptoms lasting ≥3 months were identified: age, tobacco consumption, acute bradycardia, laboratory measures of urea, and neutrophils. This exploratory, hypothesis-generating study contributes to the development of ciguatera epidemiology by narrowing the list from 37 possible predictors to a list of five predictors that seem worth further investigation as candidate risk factors in more targeted studies of ciguatera symptom duration.