On 28 April 2021, the investigation team of the Department of Disease Control, Ministry of Public Health, was notified of a cluster of people developing neurological symptoms following COVID-19 vaccination in a province in eastern Thailand. We conducted an investigation from 29 April to 20 May 2021 to confirm the outbreak, describe the epidemiological characteristics and identify possible risk factors. A matched case-control study was conducted. Matching factors were gender and vaccination site. A confirmed case was a person receiving COVID-19 vaccination in the province and developed at least one neurological symptom between 21 April and 20 May 2021. The rapid assessment of the vaccination cold chain system was carried out. We found a total of 36 cases out of 3920 vaccinees (attack rate = 0.92%), all cases were recovered and classified as an immunization stress-related reaction (ISRR) by the National AEFI Expert Committee. An analytic study found that menstruation was significantly associated with ISRR (AOR = 6.84 [95%CI = 1.09–42.91]). The environmental survey suggested that the cold chain system was properly managed. Further studies on other precipitating causes of ISRR should be performed. In terms of recommendation, health providers should pay greater attention to women menstruating during and after COVID-19 immunization.
Background We investigate the completeness of contact tracing for COVID-19 during the first wave of the COVID-19 pandemic in Thailand, from early January 2020 to 30 June 2020. Methods Uni-list capture-recapture models were applied to the frequency distributions of index cases to inform two questions: (1) the unobserved number of index cases with contacts, and (2) the unobserved number of index cases with secondary cases among their contacts. Results Generalized linear models (using Poisson and logistic families) did not return any significant predictor (age, sex, nationality, number of contacts per case) on the risk of transmission and hence capture-recapture models did not adjust for observed heterogeneity. Best fitting models, a zero truncated negative binomial for question 1 and zero-truncated Poisson for question 2, returned sensitivity estimates for contact tracing performance of 77.6% (95% CI = 73.75–81.54%) and 67.6% (95% CI = 53.84–81.38%), respectively. A zero-inflated negative binomial model on the distribution of index cases with secondary cases allowed the estimation of the effective reproduction number at 0.14 (95% CI = 0.09–0.22), and the overdispersion parameter at 0.1. Conclusion Completeness of COVID-19 contact tracing in Thailand during the first wave appeared moderate, with around 67% of infectious transmission chains detected. Overdispersion was present suggesting that most of the index cases did not result in infectious transmission chains and the majority of transmission events stemmed from a small proportion of index cases.
Objectives: The objective of this study was to evaluate and injury surveillance (IS) system's ability to monitor road traffic deaths and the coverage of road traffic injury and death surveillance in Phuket, Thailand. Methods: U.S. Centers for Disease Control and Prevention guidelines on surveillance system evaluation were used to qualitatively and quantitatively evaluate IS. Interviews with key stakeholders focused on IS's usefulness, simplicity, flexibility, acceptability, and stability. Active case finding of 2014 road traffic deaths in all paper and electronic hospital record systems was used to assess system sensitivity, positive predictive value, and data quality. Electronic data matching software was used to determine the implications of combining IS data with other provincial-level data sources (e.g., death certificates, electronic vehicle insurance claim system). Results: Evaluation results indicated that IS was useful, flexible, acceptable, and stable, with a high positive predictive value (99%). Simplicity was limited due to the burden of collecting data on all injuries and use of paper-based data collection forms. Sensitivity was low, with IS only identifying 55% of hospital road traffic death cases identified during active case finding; however, IS cases were representative of cases identified. Data accuracy and completeness varied across data fields. Combining IS with active case finding, death certificates, and the electronic vehicle insurance claim system more than doubled the number of road traffic death cases identified in Phuket.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.