Dengue Hemorrhagic Fever (DHF) is a major mosquito-borne viral disease. Studies have reported a strong correlation between weather, the abundance of Aedes aegypti, the vector of DHF virus, and dengue incidence. However, this conclusion has been based on the general climate pattern of wide regions. In general, however, the human population, level of infrastructure, and land-use change in rural and urban areas often produce localized climate patterns that may influence the interaction between climate, vector abundance, and dengue incidence. Thoroughly understanding this correlation will allow the development of a customized and precise local early warning system. To achieve this purpose, we conducted a cohort study, during January-December 2017, in 16 districts in Bandung, West Java, Indonesia. In the selected areas, local weather stations and modified light mosquito traps were set up to obtain data regarding daily weather and the abundance of adult female Ae. aegypti. A generalized linear model was applied to analyze the effect of local weather and female adult Ae. aegypti on the number of dengue cases. The result showed a significant non-linear correlation among mosquito abundance, maximum temperature, and dengue cases. Using our model, the data showed that the addition of a single adult Ae. aegypti mosquito increased the risk of dengue infection by 1.8%, while increasing the maximum temperature by one degree decreased the risk by 17%. This finding suggests specific actionable insights needed to supplement existing mosquito eradication programs.

This study was performed to evaluate the health information system regarding the dengue surveillance system in Indonesia. Major obstacles to the implementation of an effective health information system regarding dengue cases in Bandung are examined, and practical suggestions on measures to overcome them are discussed. The study utilized a mixed-method research design using qualitative approaches: document analysis, key informants and focus group interviews. Thirty key informants were selected, comprised of policymakers, senior managers, and staff at the Ministry of Health. Data from documents and transcripts were evaluated through a modified Institutional Analysis and Development (IAD) framework described by Ostrom. Through this study, we have identified several issues that hinder the effective implementation of the health information system in the case of dengue in Bandung. In the end, we propose several recommendations for reform that encompasses motivational, strategic, and structural approaches to each component of the analysis. Through evaluation of the health information system for dengue surveillance in Indonesia, we conclude that well-coordination in multi-level governance in a country as large as Indonesia is the key in the implementation of the health information system in different levels of agencies. Furthermore, the adaptability of human resources in adopting a new information system also plays an important part.

Background: Bandung, the fourth largest city in Indonesia and capital of West Java province, has been considered a major endemic area of dengue, and studies show that the incidence in this city could increase and spread rapidly. At the same time, estimation of incidence could be inaccurate due to a lack of reliable surveillance systems. To provide strategic information for the dengue control program in the face of limited capacity, this study used spatial pattern analysis of a possible outbreak of dengue cases, through the Geographic Information System (GIS). To further enhance the information needed for effective policymaking, we also analyzed the demographic pattern of dengue cases. Methods: Monthly reports of dengue cases from January 2014 to December 2016 from 16 hospitals in Bandung were collected as the database, which consisted of address, sex, age, and code to anonymize the patients. The address was then transformed into geocoding and used to estimate the relative risk of a particular area’s developing a cluster of dengue cases. We used the kernel density estimation method to analyze the dynamics of change of dengue cases. Results: The model showed that the spatial cluster of the relative risk of dengue incidence was relatively unchanged for 3 years. Dengue high-risk areas predominated in the southern and southeastern parts of Bandung, while low-risk areas were found mostly in its western and northeastern regions. The kernel density estimation showed strong cluster groups of dengue cases in the city. Conclusions: This study demonstrated a strong pattern of reported cases related to specific demographic groups (males and children). Furthermore, spatial analysis using GIS also visualized the dynamic development of the aggregation of disease incidence (hotspots) for dengue cases in Bandung. These data may provide strategic information for the planning and design of dengue control programs.

The burden of dengue has emerged as a serious public health issue due to its impact on morbidity, mortality, and economic burden. Existing surveillance systems are inadequate to provide the necessary data for the prompt and efficient control of dengue. Passive surveillance of dengue cases may lead to underreporting and delayed mitigation responses. Improved dengue control program requires sensitive and proactive methods for early detection of dengue. We collected and reviewed existing research articles worldwide on detecting dengue virus in Aedes species larvae. Searches were conducted in PUBMED and Google Scholar, including all the studies published in English and Bahasa Indonesia. Twenty-nine studies were included in this review in terms of assay used, positivity rate, and dengue serotype detected. The presence of dengue virus in immature mosquitoes was mostly detected using reverse transcription PCR (RT-PCR) in pooled larvae. In one study, dengue virus was detected in larvae from laboratory-infected mosquitoes using enzyme-linked immunosorbent assay (ELISA). The positivity rate of dengue virus detection ranged from 0 to 50% in field-caught larvae. Although various methods can detect the dengue virus, further research encourages the use of low-cost and less laborious methods for active surveillance of dengue in larvae.

WHO declared the outbreak of COVID-19, caused by SARS-CoV-2, a pandemic in March 2020. More than 223 million cases and approximately 4.6 million deaths have been confirmed. Early diagnosis and immediate treatment became a priority during this pandemic. However, COVID-19 diagnostic testing resources are limited, especially early in the pandemic. Apart from being limited, the COVID-19 diagnostic tests using reverse transcription polymerase chain reaction (RT-PCR) have encountered storage, transportation, and safety issues. These problems are mainly experienced by developing poor countries, countries in the equatorial region, and archipelagic countries. VITPAD® is a guanidine-based inactivation transport medium (ITM) formulated to maintain the RNA quality of SARS-CoV-2 during transportation without cold chains. This study, conducted from September 2020 to March 2021, performed clinical validation of VITPAD® by comparing its performance with a globally commercially available ITM from the NEST brand. Its stability at room temperature, safety, and resistance at high temperatures was also tested using RT-PCR analysis. VITPAD® can reduce the infectious nature of the specimen, preserve the SARS-CoV-2 for 18 days at an ambient temperature, and resist high temperatures (40°C for 3 hours). A guanidine-based transport medium, such as VITPAD®, is compatible and recommended for RT-PCR-based molecular diagnosis of COVID-19.

(1) Background: This paper will present an elaboration of the risk assessment methodology by Deutsche Gesellschaft für Internationale Zusammenarbeit GmbH (GIZ), Eurac Research and United Nations University Institute for Environment and Human Security (UNU-EHS) for the assessment of dengue. (2) Methods: We validate the risk assessment model by best-fitting it with the number of dengue cases per province using the least-square fitting method. Seven out of thirty-four provinces in Indonesia were chosen (North Sumatra, Jakarta Capital, West Java, Central Java, East Java, Bali and East Kalimantan). (3) Results: A risk assessment based on the number of dengue cases showed an increased risk in 2010, 2015 and 2016 in which the effects of El Nino and La Nina extreme climates occurred. North Sumatra, Bali, and West Java were more influenced by the vulnerability component, in line with their risk analysis that tends to be lower than the other provinces in 2010, 2015 and 2016 when El Nino and La Nina occurred. (4) Conclusion: Based on data from the last ten years, in Jakarta Capital, Central Java, East Java and East Kalimantan, dengue risks were mainly influenced by the climatic hazard component while North Sumatra, Bali and West Java were more influenced by the vulnerability component.