RESUMEN
OBJECTIVE: The objective of this systematic review is to synthesize studies on economic burden and economic impact of noncommunicable diseases (NCDs) in the World Health Organization South-East Asian Region (WHO SEAR) countries. INTRODUCTION: WHO SEAR countries represent 8.6% of the world's population and 75% of all deaths in this region are attributable to NCDs. In addition, there is a pattern of low government spending on health in SEAR countries, leading to a high proportion of health financing by patients', risking impoverishment for households. INCLUSION CRITERIA: We will consider observational (cross-sectional, cohort, and case-control) and interventional (either single arm or comparative) studies that report economic burden (direct and indirect costs, out-of-pocket expenditure) and economic impact (catastrophic health expenditure, hardship financing, impoverishment, and gross domestic product impact at individual, household, and/or country levels). This includes government surveys, surveillance, and secondary data analyses for one or more NCDs prevalent in the WHO SEAR. METHODS: We will conduct a comprehensive search for relevant studies in databases, including PubMed (MEDLINE), Embase (Ovid), Scopus, Web of Science, Google Scholar, and gray literature with no date limits. Two independent reviewers will screen titles and abstracts, followed by full-text screening. Included studies will be critically appraised for quality. Data will be extracted accordingly and, if possible, random effects meta-analyses will be conducted on the pooled data for resource utilization and costs (including burden and impact), presenting the degree of variation between studies. The characteristics and results of the included studies will be narratively summarized with accompanying tables. REVIEW REGISTRATION: PROSPERO CRD42023421302.
RESUMEN
In the absence of sufficient testing capacity for COVID-19, a substantial number of infecteds are expected to remain undetected. Since the undetected cases are not quarantined, they can be expected to transmit the infection at a much higher rate than their quarantined counterparts. That is, in the absence of extensive random testing, the actual prevalence and incidence of the SARS-CoV-2 infection can be significantly higher than that being reported. Thus, it is imperative that the information on the percentage of undetected (or unreported) cases be incorporated in the mechanism for estimating the key epidemiological parameters, like rate of transmission, rate of recovery, reproduction rate, etc., and hence, for forecasting the transmission dynamics of the epidemic. In this paper, we have developed a new dynamic version of the basic susceptible-infected-removed (SIR) compartmental model, called the susceptible-infected (quarantined/ free) - recovered- deceased [SI(Q/F)RD] model, to assimilate the impact of the time-varying proportion of undetected cases on the transmission dynamics of the epidemic. Further, we have presented a Dirichlet-Beta state-space formulation of the SI(Q/F)RD model for the estimation of its parameters using posterior realizations from the Gibbs sampling procedure. As a demonstration, the proposed methodology has been implemented to forecast the COVID-19 transmission in California and Florida. Results suggest significant amount of underreporting of cases in both states. Further, posterior estimates obtained from the state-space SI(Q/F)RD model show that average reproduction numbers associated with the undetected infectives [California: 1.464; Florida: 1.612] are substantially higher than those associated with the quarantined infectives [California: 0.497; Florida: 0.359]. The long-term forecasts of death counts show trends similar to those of the estimates of excess deaths for the comparison period post training data timeline.