BackgroundThis study focused on evaluating the fumigation scheme and identifying problems encountered during the operation in the Bangkok Metropolitan Administration area.MethodsTen district health officers working in different fumigation teams of the dengue outbreak control programme around Bangkok had participated in an in-depth interview. Five predetermined themes, including (i) dengue surveillance and control strategy, (ii) quality and availability of equipment, (iii) delays, (iv) human resources, and (v) area coverage, and other emerging themes were addressed during the interviews.ResultsAlthough the staff seemed to know the operation protocol of the dengue surveillance and control programmes well, they encountered some difficulties in accessing households for proper spraying, and a lack of human and material resources, especially during an outbreak. Other emerging themes concerned inefficient communications among the sectors from hospital to district offices, leading to inaccurate or missing patient addresses for spraying, and the lack of community networks and public cooperation for the dengue control programmes.ConclusionsThe findings suggest that coordination among the relevant health sectors to acquire accurate and timely information about dengue cases is essential. Involving community networks should help to improve public engagement with and participation in the surveillance and outbreak control programmes.

Summary. Half-dose AZD1222 or BNT162b2 boosters maintained immunogenicity and safety, and were non-inferior to full doses. All doses elicited high immunogenicity and best with extended post-CoronaVac primary-series intervals (120-180 days) and high-transmissibility Omicron. Methods. At 60-to-<90, 90-to-<120, or 120-to-180 days (intervals) post-CoronaVac primary-series, participants were randomized to full-dose or half-dose AZD1222 or BNT162b2, and followed up at day-28, -60 and -90. Vaccination-induced immunogenicity to Ancestral, Delta and Omicron BA.1 strains were evaluated by assessing anti-spike (anti-S), anti-nucleocapsid antibodies, pseudovirus neutralization (PVNT), micro-neutralization titers, and T-cells assays. Descriptive statistics and non-inferiority cut-offs were reported as geometric mean concentration (GMC) or titer (GMT) and GMC/GMT ratios comparing baseline to day-28 and day-90 seroresponses, and different intervals post-CoronaVac primary-series. Omicron immunogenicity was only evaluated in full-dose recipients. Findings. No serious or severe vaccine-related safety events occurred. All assays and intervals showed non-inferior immunogenicity between full-doses and half-doses. However, full-dose vaccines and/or longer, 120-to-180-day intervals substantially improved immunogenicity (in GMC measured by anti-S assays or GMT measured by PVNT50; p <0.001). Within platforms and regardless of dose or platform, seroconversions were over 97%, and over 90% for pseudovirus neutralizing antibodies, but similar against the SARS-CoV-2 strains. Immunogenicity waned more quickly with half-doses than full-doses between day 60-to-90 follow-ups, but remained high against Ancestral or Delta strains. Against Omicron, the day-28 immunogenicity increased with longer intervals than shorter intervals for full-dose vaccines. Interpretation. Combining heterologous schedules, fractional dosing, and extended post-second dose intervals, broadens population-level protection and prevents disruptions, especially in resource-limited settings. Funding. Funding was provided by the Program Management Unit for Competitiveness Enhancement (PMU-C) National research, National Higher Education, Science, Research and Innovation Policy Council, Thailand through Clinixir Ltd.

ObjectiveThis paper presents an investigation using early notification methods to enhancing epidemic detection in syndromic surveillance data from royal Thai army in Thailand.IntroductionEarly Notification Detection Systems have taken a critical role in providing early notice of disease outbreaks. To improve the detection methods for disease outbreaks, many detection methods have been created and implemented. However, there is limited information on the effectively of syndromic surveillance in Thailand. Knowing the performance, strengths and weakness of these surveillance systems in providing early warning for outbreaks will increase disease outbreak detection capacity in Thailand.MethodsThis study describes and compares the capabilities of various outbreak detection algorithms using 37,043 unique syndromic daily reports based on medical information from both civilian and military personnel from the Unit Base Surveillance of Royal Thai Army (RTA) along the Thai-Myanmar and Thai-Cambodia boarder areas. Traditional epidemic detection method: mean plus two SD were compared with algorithms for early notification methods and which included regression, regression/EWMA/Poisson, CDC-C1, CDC-C2 and CDC-C3. Early notification and epidemic detection methods were compared according to their ability to generate alert notifications. Sensitivity, specificity, positive predictive value (PPV), negative predictive value and overall accuracy to detect or predict disease outbreaks were estimated.ResultsThis study shows that the preliminary results are promising for epidemic detection by early notification methods in syndromic surveillance in Thailand. The majority of syndromic records were categorized into 12 symptoms. The three most common symptoms were respiratory, fever and gastrointestinal illness (11,501; 9,549 and 4,498 respectively). The results from the early notification systems were analyzed and their performances were compared with traditional epidemic detection method according to their ability to generate early warning alerts for the 3 symptoms. In our study regression/EWMA/Poisson method had higher specificity across the 3 symptoms (94.5%, 94.7% and 95.9% respectively), but generated lower sensitivity (22.6%, 40.4% and 23.1%). CDC-C1, CDC-C2 and CDC-C3 algorithms are easy to understand and are widely used. CDC-C3 had higher sensitivity to detect gradual disease outbreak effects (64.2%, 70.2% and 57.7%), but it is known to produce higher alarm rates/false positive signals.ConclusionsWithin the syndromic surveillance data of RTA, the CDC algorithm is the best chosen to use in the syndromic system due to being easy to understand and implement in a system with high sensitivity. CDC-C2 is the best early notification detection method due to its high sensitivity and PPV. However, CDC-C3 is shows the highest sensitivity, but exhibits the lowest specificity and PPV for all symptoms including a high alarm rates. To be useful, early notification detection methods must have acceptable operating characteristics. Consequently, we should select the most appropriate algorithm method to explain the data well and in order to improve detection of outbreaks. The comparison methods used in this study may be useful for testing other proposed alert threshold methods and may have further applications for other populations and other diseases.References1. Chretien JP, Burkom HS, Sedyaningsih ER, Larasati RP, et al. Syndromic Surveillance: Adapting Innovations to Developing Settings. PLoS Medicine 2008; vol 5: page 1-6.2. Burkom HS, Elbert Y, Magruder SF, Najmi AH, Peter W, Thompson MW. Developments in the roles, features, and evaluation of alerting algorithms for disease outbreak monitoring. Johns Hopkins APL Technical Digest 2008; vol 27: page 313.

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