FINDINGS: A malaria survey spanning 7 years (2006 - 2012) was conducted in Selangor. A total of 1623 laboratory confirmed malaria cases were reported from Selangor's nine districts. While 72.6% of these cases (1178/1623) were attributed to imported malaria (cases originating from other countries), 25.5% (414/1623) were local cases and 1.9% (31/1623) were considered as relapse and unclassified cases combined. In this study, the most prevalent infection was P. vivax (1239 cases, prevalence 76.3%) followed by P. falciparum (211, 13.0%), P. knowlesi (75, 4.6%), P. malariae (71, 4.4%) and P. ovale (1, 0.06%). Mixed infections comprising of P. vivax and P. falciparum were confirmed (26, 1.6%). Entomological surveys targeting the residences of malaria patients' showed that the most commonly trapped Anopheles species was An. maculatus. No oocysts or sporozoites were found in the An. maculatus collected. Nevertheless, the possibility of An. maculatus being the malaria vector in the investigated locations was high due to its persistent occurrence in these areas.
CONCLUSIONS: Malaria cases reported in this study were mostly imported cases. However the co-existence of local cases and potential Plasmodium spp. vectors should be cause for concern. The results of this survey reflect the need of maintaining closely monitored malaria control programs and continuous extensive malaria surveillance in Peninsula Malaysia.
METHODS: We reanalyzed the empirical data from the Health Insurance Plan trial in 1963 to the UK age trial in 1991 and their follow-up data published until 2015. We first performed Bayesian conjugated meta-analyses on the heterogeneity of attendance rate, sensitivity, and over-detection and their impacts on advanced stage breast cancer and death from breast cancer across trials using Bayesian Poisson fixed- and random-effect regression model. Bayesian meta-analysis of causal model was then developed to assess a cascade of causal relationships regarding the impact of both attendance and sensitivity on 2 main outcomes.
RESULTS: The causes of heterogeneity responsible for the disparities across the trials were clearly manifested in 3 components. The attendance rate ranged from 61.3% to 90.4%. The sensitivity estimates show substantial variation from 57.26% to 87.97% but improved with time from 64% in 1963 to 82% in 1980 when Bayesian conjugated meta-analysis was conducted in chronological order. The percentage of over-detection shows a wide range from 0% to 28%, adjusting for long lead-time. The impacts of the attendance rate and sensitivity on the 2 main outcomes were statistically significant. Causal inference made by linking these causal relationships with emphasis on the heterogeneity of the attendance rate and sensitivity accounted for the variation in the reduction of advanced breast cancer (none-30%) and of mortality (none-31%). We estimated a 33% (95% CI: 24-42%) and 13% (95% CI: 6-20%) breast cancer mortality reduction for the best scenario (90% attendance rate and 95% sensitivity) and the poor scenario (30% attendance rate and 55% sensitivity), respectively.
CONCLUSION: Elucidating the scenarios from high to low performance and learning from the experiences of these trials helps screening policy-makers contemplate on how to avoid errors made in ineffective studies and emulate the effective studies to save women lives.