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1.
Lancet Glob Health ; 11(9): e1412-e1421, 2023 09.
Article in English | MEDLINE | ID: mdl-37591587

ABSTRACT

BACKGROUND: The impact of the COVID-19 pandemic on tuberculosis control in high-burden countries has not been adequately assessed. We aimed to estimate the impact of the COVID-19 pandemic on the national tuberculosis programme in Indonesia, in association with indicators of human development and health-system capacity across all 514 districts in 34 provinces. METHODS: We did a nationwide longitudinal analysis to compare tuberculosis case notification, treatment coverage, and mortality rates in Indonesia before (2016-19) and during (2020-21) the COVID-19 pandemic. The following outcomes were assessed: the district-level quarterly reported tuberculosis case notification rate (number of all reported tuberculosis cases per 100 000 population), treatment coverage (proportion of tuberculosis patients who started treatment), and all-cause mortality rate in patients with tuberculosis (number of reported deaths per 100 000 population). District-level data on COVID-19 incidence and deaths, health-system capacity, and human development and sociodemographics were also analysed. Multilevel linear spline regression was done to assess quarterly time trends for the three outcomes. FINDINGS: During the COVID-19 pandemic, the tuberculosis case notification rate declined by 26% (case notification rate ratio 0·74, 95% CI 0·72-0·77) and treatment coverage declined by 11% (treatment coverage ratio 0·89, 95% CI 0·88-0·90), but there was no significant increase in all-cause mortality (all-cause mortality rate ratio 0·97, 95% CI 0·91-1·04) compared with the pre-pandemic period. In the second year of the pandemic, we observed a partial recovery of the case notification rate from Q1 to Q4 of 2021, a persistent decrease in treatment coverage, and a decrease in the all-cause mortality rate from Q2 of 2020 to Q4 of 2021. The multivariable analysis showed that the reduction in the tuberculosis case notification rate was associated with a higher COVID-19 incidence rate (adjusted odds ratio 3·1, 95% CI 1·1-8·6, for the highest compared with the lowest group) and fewer GeneXpert machines for tuberculosis diagnosis (3·1, 1·0-9·4, for the lowest compared with the highest group) per 100 000 population. The reduction in tuberculosis treatment coverage was associated with higher COVID-19 incidence (adjusted odds ratio 11·7, 95% CI 1·5-93·4, for the highest compared with the lowest group), fewer primary health centres (10·6, 4·1-28·0, for the lowest compared with the middle-high group), and a very low number of doctors (0·3, 0·1-0·9, for the low-middle compared with the lowest group) per 100 000 population. No factors were shown to be significantly associated with all-cause mortality. INTERPRETATION: The COVID-19 pandemic adversely and unevenly affected the national tuberculosis programme across Indonesia, with the greatest impacts observed in districts with the lowest health-system capacity. These disruptions could lead to an escalation in tuberculosis transmission in the coming years, warranting the need for intensified efforts to control tuberculosis and strengthen local health systems. FUNDING: Wellcome Africa Asia Programme Vietnam. TRANSLATION: For the Bahasa translation of the abstract see Supplementary Materials section.


Subject(s)
COVID-19 , Humans , Indonesia/epidemiology , COVID-19/epidemiology , Pandemics , Asia , Africa
2.
BMC Public Health ; 23(1): 103, 2023 01 14.
Article in English | MEDLINE | ID: mdl-36641453

ABSTRACT

BACKGROUND: Ensuring health equity, especially for vulnerable populations in less developed settings with poor health system is essential for the current and future global health threats. This study examined geographical variations of COVID-19 mortality and its association with population health characteristics, health care capacity in responding pandemic, and socio-economic characteristics across 514 districts in Indonesia. METHODS: This nationwide ecological study included aggregated data of COVID-19 cases and deaths from all 514 districts in Indonesia, recorded in the National COVID-19 Task Force database, during the first two years of the epidemic, from 1 March 2020 to 27 February 2022. The dependent variable was district-level COVID-19 mortality rate per 100,000 populations. The independent variables include district-level COVID-19 incidence rate, population health, health care capacity, and socio-demographics data from government official sources. We used multivariable ordinal logistic regression to examine factors associated with higher mortality rate. RESULTS: Of total 5,539,333 reported COVID-19 cases, 148,034 (2.7%) died, and 5,391,299 (97.4%) were recovered. The district-level mortality rate ranged from 0 to 284 deaths per 100,000 populations. The top five districts with the highest mortality rate were Balikpapan (284 deaths per 100,000 populations), Semarang (263), Madiun (254), Magelang (250), and Yogyakarta (247). A higher COVID-19 incidence (coefficient 1.64, 95% CI 1.22 to 1.75), a higher proportion of ≥ 60 years old population (coefficient 0.26, 95% CI 0.06 to 0.46), a higher prevalence of diabetes mellitus (coefficient 0.60, 95% CI 0.37 to 0.84), a lower prevalence of obesity (coefficient -0.32, 95% CI -0.56 to -0.08), a lower number of nurses per population (coefficient -0.27, 95% CI -0.50 to -0.04), a higher number of midwives per population (coefficient 0.32, 95% CI 0.13 to 0.50), and a higher expenditure (coefficient 0.34, 95% CI 0.10 to 0.57) was associated with a higher COVID-19 mortality rate. CONCLUSION: COVID-19 mortality rate in Indonesia was highly heterogeneous and associated with higher COVID-19 incidence, different prevalence of pre-existing comorbidity, healthcare capacity in responding the pandemic, and socio-economic characteristics. This study revealed the need of controlling both COVID-19 and those known comorbidities, health capacity strengthening, and better resource allocation to ensure optimal health outcomes for vulnerable population.


Subject(s)
COVID-19 , Diabetes Mellitus , Humans , Middle Aged , COVID-19/epidemiology , Indonesia/epidemiology , Diabetes Mellitus/epidemiology , Comorbidity , Pandemics
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