Characterization of spatial and temporal transmission of HIV infection in Surabaya, Indonesia: Geographic information system (GIS) cluster detection analysis (2016-2020).

The high prevalence of human immunodeficiency virus (HIV) infections has become a devastating public health problem in Indonesia. In response, the government has taken measures to reduce the transmission of HIV and the number of deaths from HIV/acquired immunodeficiency syndrome (AIDS). However, these efforts have not successfully reduced the spread of HIV in Surabaya. In this study, we analyzed the factors that could influence the spread of HIV in Surabaya using a Geographic Information System. We conducted a spatial analysis of HIV/AIDS clusters in Surabaya from 2016 to 2020. Spatial autocorrelation and spatiotemporal analysis were used to identify local HIV clustering. In addition, the Global Moran's I index was applied to detect HIV clustering at the sub-district level. The results showed that HIV mostly occurred among males (683/969; 70.3%) in the economic age group (20-35 years) and that the infection was transmitted mostly through sexual intercourse (942/969; 97.2%). The hotspots were located in Central and Southern Surabaya, including the Genteng, Tegal Sari, Gubeng, and Sawahan sub-sub-districts. Western Surabaya (Benowo and Pakal) was the only hot spot in 2018. In conclusion, the spatial and temporal analysis of HIV, coupled with an assessment of the factors that drive the epidemic, can assist the government to formulate policies and design targeted interventions to prevent and control the epidemic in Surabaya, Indonesia.

A household survey of intrafamily norovirus transmission.

Norovirus (NoV) is a leading cause of epidemic and sporadic gastroenteritis in people of all ages. Humans are the primary source of NoV and household contact is one of the risk factors for NoV transmission. However, the mechanisms underlying person-to-person NoV transmission are poorly understood. Here we conducted a survey to profile the frequency and characteristics of intrafamily NoV transmission. Stool samples were collected every week from three households between 2016 and 2020; the total number of samples was 1105. The detection of NoV and the genotyping were performed by reverse transcription-polymerase chain reaction targeting the capsid region and direct sequencing methods. NoV was detected in 3.4% of all samples. Eight NoV genotypes were identified. The most common genotype was GII.17, followed in order by GII.6, GI.6, GII.4, GI.3, and GI.2/GI.8/GI.9. Most NoV-positive samples were obtained from asymptomatic individuals. The highest number of NoV transmissions was found in household 3 (6 infections), followed by household 2 (2 infections), while household 1 had no NoV transmission, suggesting that asymptomatic NoV carriers play a major role in infection as NoV reservoirs in the households. Further clarification of the mode of infection will contribute to improved understanding and an appropriate prevention.

Effects of Ambient Temperature, Relative Humidity, and Precipitation on Diarrhea Incidence in Surabaya.

BACKGROUND: Diarrhea remains a common infectious disease caused by various risk factors in developing countries. This study investigated the incidence rate and temporal associations between diarrhea and meteorological determinants in five regions of Surabaya, Indonesia. METHOD: Monthly diarrhea records from local governmental health facilities in Surabaya and monthly means of weather variables, including average temperature, precipitation, and relative humidity from Meteorology, Climatology, and Geophysical Agency were collected from January 2018 to September 2020. The generalized additive model was employed to quantify the time lag association between diarrhea risk and extremely low (5th percentile) and high (95th percentile) monthly weather variations in the north, central, west, south, and east regions of Surabaya (lag of 0-2 months). RESULT: The average incidence rate for diarrhea was 11.4 per 100,000 during the study period, with a higher incidence during rainy season (November to March) and in East Surabaya. This study showed that the weather condition with the lowest diarrhea risks varied with the region. The diarrhea risks were associated with extremely low and high temperatures, with the highest RR of 5.39 (95% CI 4.61, 6.17) in the east region, with 1 month of lag time following the extreme temperatures. Extremely low relative humidity increased the diarrhea risks in some regions of Surabaya, with the highest risk in the west region at lag 0 (RR = 2.13 (95% CI 1.79, 2.47)). Extremely high precipitation significantly affects the risk of diarrhea in the central region, at 0 months of lag time, with an RR of 3.05 (95% CI 2.09, 4.01). CONCLUSION: This study identified a high incidence of diarrhea in the rainy season and in the deficient developed regions of Surabaya, providing evidence that weather magnifies the adverse effects of inadequate environmental sanitation. This study suggests the local environmental and health sectors codevelop a weather-based early warning system and improve local sanitation practices as prevention measures in response to increasing risks of infectious diseases.

Mortality and morbidity associated with ambient temperatures in Taiwan.

BACKGROUND: This study evaluated integrated risks of all-cause mortality, emergency room visits (ERVs), and outpatient visits associated with ambient temperature in all cities and counties of Taiwan. In addition, the modifying effects of socio-economic and environmental factors on temperature-health associations were also evaluated. METHODS: A distributed lag non-linear model was applied to estimate the cumulative relative risks (RRs) with confidence intervals of all-cause mortality, ERVs, and outpatient visits associated with extreme temperature events. Random-effect meta-analysis was used to estimate the pooled RR of all-cause mortality, ERVs, and outpatient visits influenced by socio-economic and environmental factors. RESULTS: Temperature-related risks varied with study area and health outcome. Meta-analysis showed greater all-cause mortality risk occurred in low temperatures than in high temperatures. Integrated RR of all-cause mortality was 1.71 (95% confidence interval [CI]:1.43-2.04) in the 5th percentile temperature and 1.10 (95% CI: 1.05-1.15) in the 95th percentile temperature, while the lowest mortality risk was in the 60th percentile temperature (22.2 °C). Risk for ERVs increased when temperature increased (RR was 1.21 [95% CI: 1.17-1.26] in 95th percentile temperature), but risk of outpatient visits increased at low temperatures (RR was 1.06 [95% CI: 1.01-1.12] in the 5th percentile temperature). Certain socio-economic factors significantly modified low-temperature-related mortality risks, including number of employed populations, elders living alone from lower-income families, and public and medical services. CONCLUSIONS: This study found that mortality and outpatient visits were higher at low temperature, while ERVs risk was higher at high temperature. Future plans for public health and emerging medical services responding to extreme temperatures should consider regional and integrated evaluations of temperature-related health risks and modifying factors.