ASSESSING OF THAILAND HIV DATA QUALITY AND ITS IMPACT TO UNAIDS 90-90-90

Introduction Despite having an effective Anti-Retroviral therapy regimen that improves the quality of life of HIV patients, HIV is still a major threat to public health and still is growing. To address this threat, UNAIDS has established the policy of the 90-90-90 indicators that needed to be achived. In 2018, Thailand’s indicators have become unreasonably high excessing 100%. Therefore, this study aims to assess the current data quality using the Ministry of Public Health, exploring the causes, and providing recommendations. Methods Using a mix-methods approach this study analyzes and compares across two databases, the Ministry of Public Health (MOPH) and National AIDS Program (NAP) to describe the overall quality and the extent of the two data sources difference. The province with the highest difference was selected for a field visit and the deployment of the Data Quality Improvement Tools (DQI Tools), jointly developed by MOPH and Thai-MOPH-US-CDC Collaborator (TUC) for assessing the HIV data quality. Field interviews were conducted using the MEASURE Data Quality Audit (DQA) as a guide to identifying the drop-off in the workflow. Results Thailand's 90-90-90 indicators were calculated using NAP as a default data source giving 105%,72%, and 83% respectively. For MOPH, the first indicator was 104% and 52% for the second indicator. The third indicator for the MOPH was not available because of a lack of laboratory data. NAP data quality gaps were identified including a legacy data migration problem and a difficult data correction process. MOPH gaps were related to the lacking of a single unified standard for both laboratory and medication, unclear regulation, and lack of incentives for data reporting. Bangkok, while having a similar reporting practices to the non-Bangkok province, it also suffers from having several hospital affiliations, technical problems, and limited data stewardship. Conclusion In this study, NAP suffers from complicated data correction processes, coverage of other health schemes, and disincentive, it was a suitable source for the 90-90-90 indicator calculation. MOPH is not suitable for indicator calculation from lacking national data standards, unclear regulation, and the database structure itself. Bangkok, Thailand's capital city is the area that needs special attention

ASSESSING OF THAILAND HIV DATA QUALITY AND ITS IMPACT TO UNAIDS 90-90-90

Introduction Despite having an effective Anti-Retroviral therapy regimen that improves the quality of life of HIV patients, HIV is still a major threat to public health and still is growing. To address this threat, UNAIDS has established the policy of the 90-90-90 indicators that needed to be achived. In 2018, Thailand’s indicators have become unreasonably high excessing 100%. Therefore, this study aims to assess the current data quality using the Ministry of Public Health, exploring the causes, and providing recommendations. Methods Using a mix-methods approach this study analyzes and compares across two databases, the Ministry of Public Health (MOPH) and National AIDS Program (NAP) to describe the overall quality and the extent of the two data sources difference. The province with the highest difference was selected for a field visit and the deployment of the Data Quality Improvement Tools (DQI Tools), jointly developed by MOPH and Thai-MOPH-US-CDC Collaborator (TUC) for assessing the HIV data quality. Field interviews were conducted using the MEASURE Data Quality Audit (DQA) as a guide to identifying the drop-off in the workflow. Results Thailand's 90-90-90 indicators were calculated using NAP as a default data source giving 105%,72%, and 83% respectively. For MOPH, the first indicator was 104% and 52% for the second indicator. The third indicator for the MOPH was not available because of a lack of laboratory data. NAP data quality gaps were identified including a legacy data migration problem and a difficult data correction process. MOPH gaps were related to the lacking of a single unified standard for both laboratory and medication, unclear regulation, and lack of incentives for data reporting. Bangkok, while having a similar reporting practices to the non-Bangkok province, it also suffers from having several hospital affiliations, technical problems, and limited data stewardship. Conclusion In this study, NAP suffers from complicated data correction processes, coverage of other health schemes, and disincentive, it was a suitable source for the 90-90-90 indicator calculation. MOPH is not suitable for indicator calculation from lacking national data standards, unclear regulation, and the database structure itself. Bangkok, Thailand's capital city is the area that needs special attention

Evaluation of Possible Dengue Outbreak Detection Methodologies for Thailand, which one should be implemented?

Dengue has become a more impact vector-borne disease than malaria globally in both morbidity distribution and economic resources. The burdens of Dengue in Thailand seem to be one of the highest in the South-East Asia Region of the World Health Organization (WHO). Current WHO’s Dengue Strategic Plan is to improve the countries’ capacity for early detection to allow timely outbreak prevention and control. However, there are only few published research papers that address the use, implementation and evaluation of novel early detection methodologies. This is a first national operational research project with objectives to study the feasibility of implementing modern dengue outbreak detection methodologies and to evaluate these methods at better alternatives to the current outbreak detection method (median-5-years) in Thailand. We conducted a descriptive Ecological study from a complete Dengue dataset retrieved from the Department of Epidemiology, Ministry of Public Health, Thailand. During 2003-2015, there were 1,014,201 visits and 13 outbreaks of Dengue virus with the largest attack in 2013. While each of the studied detection methods displayed unique characteristics, we observed similar values of the averages and medians, upper Confidence Intervals (CI)and percentiles across three methods. Same period media-5-years might be good for alert threshold. EARS methods were able to detect every outbreak but they did not provide information on outbreak long-term trend or magnitude. Moving percentiles or upper CI could provide information for long-term trends and epidemic thresholds. Off-seasonal median or average might be suitable for seasonal thresholds. Each detection method has its own strengths and weaknesses, thus implementing these methodologies could be of great epidemiological assistance local public health surveillance systems and for early Dengue outbreak detection

Evaluation of Possible Dengue Outbreak Detection Methodologies for Thailand, which one should be implemented?

Dengue has become a more impact vector-borne disease than malaria globally in both morbidity distribution and economic resources. The burdens of Dengue in Thailand seem to be one of the highest in the South-East Asia Region of the World Health Organization (WHO). Current WHO’s Dengue Strategic Plan is to improve the countries’ capacity for early detection to allow timely outbreak prevention and control. However, there are only few published research papers that address the use, implementation and evaluation of novel early detection methodologies. This is a first national operational research project with objectives to study the feasibility of implementing modern dengue outbreak detection methodologies and to evaluate these methods at better alternatives to the current outbreak detection method (median-5-years) in Thailand. We conducted a descriptive Ecological study from a complete Dengue dataset retrieved from the Department of Epidemiology, Ministry of Public Health, Thailand. During 2003-2015, there were 1,014,201 visits and 13 outbreaks of Dengue virus with the largest attack in 2013. While each of the studied detection methods displayed unique characteristics, we observed similar values of the averages and medians, upper Confidence Intervals (CI)and percentiles across three methods. Same period media-5-years might be good for alert threshold. EARS methods were able to detect every outbreak but they did not provide information on outbreak long-term trend or magnitude. Moving percentiles or upper CI could provide information for long-term trends and epidemic thresholds. Off-seasonal median or average might be suitable for seasonal thresholds. Each detection method has its own strengths and weaknesses, thus implementing these methodologies could be of great epidemiological assistance local public health surveillance systems and for early Dengue outbreak detection

Hepatitis E in Southeast Asia

Hepatitis E is a major cause of acute viral hepatitis in the world. The causative agent of hepatitis E is hepatitis E virus (HEV). In Southeast Asia, the seroprevalence of HEV and the most prevalent genotype of HEV are largely unclear and the available data is either limited or outdated. After a systematic review of literature, we found the seroprevalence of HEV and the most prevalent genotype of HEV appear to vary greatly by countries. The seroprevalence is likely between 17% to 42% and the prevalent genotypes across Southeast Asia are likely 1, 3, and 4, but not 2 as no cases of genotype 2 have been reported in this region. As HEV remains widespread in Southeast Asia and the clinical implications of HEV can be severe, surveillance programs for HEV should be implemented

Coronavirus Disease 2019 (COVID-19) and Its Gastrointestinal and Hepatic Manifestations

Coronavirus disease 2019 (COVID-19) is a severe respiratory disease caused by the virus SARS-CoV-2 that became classified as a pandemic on March 11, 2020. COVID-19 is known to produce similar clinical manifestations to SARS of the last decade. Fever, dry cough, fatigue, myalgia, dyspnea, and sore throat are some of the most common symptoms and the median incubation period is around 4 days. While the respiratory manifestations have been widely reported, clinical manifestations on the gastrointestinal and hepatic side have often been overlooked. Diarrhea and nausea or vomiting have been reported in approximately 1-5% of cases and sometimes they precede respiratory symptoms. COVID-19 has also been reported to cause hemorrhagic colitis in one case Live SARS-CoV-2 have been detected in stool so, there is a possibility of fecal-oral transmission thus it recommended that non-urgent and low prior endoscopies be postponed. For endoscopies that cannot be postponed, SARS-CoV-2 screening of patients, minimal personnel, infection control training, and usage of negative pressure rooms are recommended. Evidence of abnormal liver-associated biomarker values have been commonly reported, however, there is evidence of extrahepatic causes those abnormal biomarker values. The evidence suggest that COVID-19 patients can have true liver injury, however, it is mild and the abnormal liver-associated biomarker values may be caused, at least partially, but muscle injury. Drugs with hepatotoxicity should be used with increased caution in COVID-19 patients