BMC Infectious Diseases · 2014 · 38 citations · 23 references
Veterinary MedicineInfectious Disease ControlInfectious DiseasesEpidemiologic MethodsEpidemiologyInfectious Disease EpidemiologyDisease EpidemiologyViral EpidemiologyViral HepatitisData Gaps AssessmentEpidemiologic Data SourcesHepatitis C InfectionHepatitis C Virus TransmissionInfection Prevalence StudiesNational PrevalencePublic Health Response EvaluationViral Hepatitis Prevention
BACKGROUND: Collecting adequate information on key epidemiological indicators is a prerequisite to informing a public health response to reduce the impact of hepatitis C virus (HCV) infection in Malaysia. Our goal was to overcome the acute data shortage typical of low/middle income countries using statistical modelling to estimate the national HCV prevalence and the distribution over transmission pathways as of the end of 2009. METHODS: Multi-parameter evidence synthesis methods were applied to combine all available relevant data sources - both direct and indirect - that inform the epidemiological parameters of interest. RESULTS: An estimated 454,000 (95% credible interval [CrI]: 392,000 to 535,000) HCV antibody-positive individuals were living in Malaysia in 2009; this represents 2.5% (95% CrI: 2.2-3.0%) of the population aged 15-64 years. Among males of Malay ethnicity, for 77% (95% CrI: 69-85%) the route of probable transmission was active or a previous history of injecting drugs. The corresponding proportions were smaller for male Chinese and Indian/other ethnic groups (40% and 71%, respectively). The estimated prevalence in females of all ethnicities was 1% (95% CrI: 0.6 to 1.4%); 92% (95% CrI: 88 to 95%) of infections were attributable to non-drug injecting routes of transmission. CONCLUSIONS: The prevalent number of persons living with HCV infection in Malaysia is estimated to be very high. Low/middle income countries often lack a comprehensive evidence base; however, evidence synthesis methods can assist in filling the data gaps required for the development of effective policy to address the future public health and economic burden due to HCV.
23
R: A Language and Environment for Statistical Computing
R Core Team · 2000 · 353K citations · Full text
Natural Sciences, Computer Science, Statistical Computing +10
The BUGS project: Evolution, critique and future directions
David J. Lunn, David J. Spiegelhalter, Andrew C. Thomas et al. · Statistics in Medicine · 2009 · 1.9K citations
Andrew Thomas, Robert O'Hara, Uwe Ligges et al. · 2006 · 650 citations