METHOD: Newly diagnosed CRC cases between 2010 and 2016 in Malaysia were identified from the National Cancer Registry. Residential addresses were geocoded. Clustering analysis was subsequently performed to examine the spatial dependence between CRC cases. Differences in socio-demographic characteristics of individuals between the clusters were also compared. Identified clusters were categorized into urban and semi-rural areas based on the population background.
RESULT: Most of the 18 405 individuals included in the study were male (56%), aged between 60 and 69 years (30.3%) and only presented for care at stages 3 or 4 of the disease (71.3%). The states shown to have CRC clusters were Kedah, Penang, Perak, Selangor, Kuala Lumpur, Melaka, Johor, Kelantan, and Sarawak. The spatial autocorrelation detected a significant clustering pattern (Moran's Index 0.244, p< 0.01, Z score >2.58). CRC clusters in Penang, Selangor, Kuala Lumpur, Melaka, Johor, and Sarawak were in urbanized areas, while those in Kedah, Perak and Kelantan were in semi-rural areas.
CONCLUSION: The presence of several clusters in urbanized and semi-rural areas implied the role of ecological determinants at the neighbourhood level in Malaysia. Such findings could be used to guide the policymakers in resource allocation and cancer control.
METHODS: This study was conducted with 314 participants from Delhi's Sanjay Colony, divided into control and intervention groups. The study spanned 14 months (August 2020 to September 2021). The intervention program comprised two educational sessions held one month apart, covering dengue awareness, health self-care, and environmental maintenance. Data were collected at baseline, after each intervention session, and during a final follow-up assessment three months later.
RESULTS: The primary outcome, the house index (HI), revealed statistically significant differences (P<0.001) favoring the intervention group. The total score (TS) for mosquito-borne disease, TS of knowledge, TS of attitude, and TS of practices all exhibited significant improvements in the intervention group. Participants showed an enhanced understanding of dengue causes, symptoms, and mosquito behavior related to breeding and biting. The HI in the intervention group decreased significantly from 21.65% to 4.45% (P<0.05).
CONCLUSION: This study, grounded in the health belief model (HBM), demonstrated the effectiveness of the intervention program in reducing HI and improving knowledge and preventive practices regarding dengue fever in impoverished urban neighborhoods of Delhi. The intervention program may be beneficial in such a poor urban community.
METHODS: In this study undertaken between April and May 2015, a total of 277 adult participants were recruited from households across three localities in the Sungai Segamat subdistrict in Segamat district. Sera were tested for immunoglobulin G (IgG) (Panbio® Dengue Indirect IgG ELISA/high-titer capture) and immunoglobulin M (IgM) (Panbio®) antibodies. The plaque reduction neutralization test (PRNT) was conducted on random samples of IgG-positive sera for further confirmation. Medical history and a recall of previous history of dengue were collected through interviews, whereas sociodemographic information was obtained from an existing database.
RESULTS: The overall seroprevalence for DENV infection was 86.6% (240/277) (95% CI: 83-91%). Serological evidence of recent infection (IgM/high-titer capture IgG) was noted in 11.2% (31/277) of participants, whereas there was evidence of past infection in 75.5% (209/277) of participants (indirect IgG minus recent infections). The PRNT assay showed that the detected antibodies were indeed specific to DENV. The multivariate analysis showed that the older age group was significantly associated with past DENV infections. Seropositivity increased with age; 48.5% in the age group of <25 years to more than 85% in age group of >45 years (P
METHODS: Data were derived from a respondent-driven survey sample (RDS) collected during 2010 of 460 PWID in greater Kuala Lumpur. Analysis focused on socio-demographic, clinical, behavioural, and network information. Spatial probit models were developed based on a distinction between the influence of peers (individuals nominated through a recruitment network) and neighbours (residing a close distance to the individual). The models were expanded to account for the potential influence of the network formation.
RESULTS: Recruitment patterns of HIV-infected PWID clustered both spatially and across the recruitment networks. In addition, HIV-infected PWID were more likely to have peers and neighbours who inject with clean needles were HIV-infected and lived nearby (<5km), more likely to have been previously incarcerated, less likely to use clean needles (26.8% vs 53.0% of the reported injections, p<0.01), and have fewer recent injection partners (2.4 vs 5.4, p<0.01). The association between the HIV status of peers and neighbours remained significantly correlated even after controlling for unobserved variation related to network formation and sero-sorting.
CONCLUSION: The relationship between HIV status across networks and space in Kuala Lumpur underscores the importance of these factors for surveillance and prevention strategies, and this needs to be more closely integrated. RDS can be applied to identify injection network structures, and this provides an important mechanism for improving public health surveillance, accessing high-risk populations, and implementing risk-reduction interventions to slow HIV transmission.