Journal
PLOS NEGLECTED TROPICAL DISEASES
Volume 9, Issue 9, Pages -Publisher
PUBLIC LIBRARY SCIENCE
DOI: 10.1371/journal.pntd.0004033
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Funding
- Medical Research Council UK [G1100449]
- British Medical Association
- Sir Halley Stewart Trust
- World Health Organisation
- Medical Research Council [G1100449] Funding Source: researchfish
- National Institute for Health Research [ACF-2011-13-004] Funding Source: researchfish
- MRC [G1100449] Funding Source: UKRI
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Background Rheumatic heart disease (RHD) is considered a major public health problem in developing countries, although scarce data are available to substantiate this. Here we quantify mortality from RHD in Fiji during 2008-2012 in people aged 5-69 years. Methods and Findings Using 1,773,999 records derived from multiple sources of routine clinical and administrative data, we used probabilistic record-linkage to define a cohort of 2,619 persons diagnosed with RHD, observed for all-cause mortality over 11,538 person-years. Using relative survival methods, we estimated there were 378 RHD-attributable deaths, almost half of which occurred before age 40 years. Using census data as the denominator, we calculated there were 9.9 deaths (95% CI 9.8-10.0) and 331 years of life-lost (YLL, 95% CI 330.4-331.5) due to RHD per 100,000 person-years, standardised to the portion of the WHO World Standard Population aged 0-69 years. Valuing life using Fiji's per-capita gross domestic product, we estimated these deaths cost United States Dollar $6,077,431 annually. Compared to vital registration data for 2011-2012, we calculated there were 1.6-times more RHD-attributable deaths than the number reported, and found our estimate of RHD mortality exceeded all but the five leading reported causes of premature death, based on collapsed underlying cause-of-death diagnoses. Conclusions Rheumatic heart disease is a leading cause of premature death as well as an important economic burden in this setting. Age-standardised death rates are more than twice those reported in current global estimates. Linkage of routine data provides an efficient tool to better define the epidemiology of neglected diseases.
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