International journal of epidemiology最新文献

Background: During the Zika virus (ZIKV) epidemic in Brazil, regional disparities in yellow fever (YF) vaccination coverage and microcephaly incidence led to the hypothesis that maternal YF vaccination could protect against ZIKV infection and microcephaly.

Methods: This case-cohort study was conducted in Campo Grande, Brazil, from 2018 to 2022 and included children with confirmed in utero ZIKV exposure (2015-2018) and a matched control group, totaling 129 mother-child dyads. Maternal blood samples were collected to assess ZIKV exposure and neutralizing YF vaccine-induced antibody (NAb) titers. Associations between YF NAb titer, congenital anomalies, and infant neurodevelopmental delay were evaluated.

Results: Mean YF NAb titers differed between ZIKV-exposed and unexposed mothers (P = .011) and between mothers of children with and without microcephaly (P = .037). Congenital anomalies were associated with lower YF NAb titers (P < .001), prenatal ZIKV exposure (P = .001), and lower family income (P < .001). Neurodevelopmental delay was associated with prenatal ZIKV exposure [adjusted odds ratio (aOR): 4.35, 95% confidence interval (CI): 1.65-13.03], prenatal care with at least six visits (aOR: 0.22, CI: 0.06-0.78), and adequate or large for gestational age birth weight (aOR: 0.09, CI: 0.01-0.44).

Conclusion: Differences in maternal YF NAb titers by ZIKV exposure and microcephaly suggest a potential protective effect of YF vaccination against ZIKV acquisition and/or development of microcephaly, which should be investigated. Developmental delay, although not associated with maternal YF immunity, was associated with antenatal ZIKV exposure, less prenatal care visits, and being small for gestational age.

Background: Country-level estimates can mask local geographic variations in progress toward achieving World Health Organization's End TB targets. This study aimed to identify spatial variations in progress toward achieving the TB incidence reduction target at a district level in Ethiopia.

Methods: A Bayesian linear regression model with a conditional autoregressive prior structure was developed to identify drivers of spatial variations in TB incidence reduction across districts and to identify spatial patterns and variations in TB incidence reduction across Ethiopia from 2015 to 2020.

Results: The national average TB incidence reduction was 31%. Ten out of 14 regions achieved a reduction of >20% in TB incidence. Out of 641 districts, 395 (61.6%) met the 20% reduction target, predominantly in the Oromia, Amhara, and South Ethiopia regions. Spatial clustering of decreased incidence reduction was noted in the Afar, Benishangul-Gumuz, and Somali regions. Factors associated with the percentage reduction in TB incidence include a 1% increase in the proportion of individuals with good TB knowledge [β: 4.23%; 95% credible interval (CrI): 1.6, 6.9], a 1-unit increase in the TB service readiness index (β: 3.41%; 95% CrI: 0.89, 6.1), and a 1-km increase in the distance from the international border (β: 2.63%; 95% CrI: 0.02, 5.10).

Conclusion: Geographic disparities in TB incidence reduction persist in Ethiopia, with only some districts achieving the national reduction targets. Targeted interventions, such as improving TB service readiness and enhancing awareness through education, are crucial to addressing these gaps, particularly in regions such as Afar, Benishangul-Gumuz, and Somali.

Background: Existing longitudinal cohort study data and associated biospecimen libraries provide abundant opportunities to efficiently examine new hypotheses through retrospective specimen testing. Outcome-dependent sampling (ODS) methods offer a powerful alternative to random sampling when testing all available specimens is not feasible or biospecimen preservation is desired. For repeated binary outcomes, a common ODS approach is to extend the case-control framework to the longitudinal setting.For ODS designs, we consider the impact of incomplete follow-up when missingness is completely at random (MCAR), missing at random (MAR), and missing not at random (MNAR). We further consider sampling from (i) complete cases, in which, in an attempt to maximize power, participants who dropped out before study completion were excluded; and (ii) all individuals, including those with incomplete follow-up.

Methods: Simulation studies based on the Advancing Clinical Therapeutics Globally HIV Infection, Aging, and Immune Function Long-Term Observational Study cohort were used to examine the impact of MCAR, MAR, and MNAR missingness, assuming specimens were sampled from either (i) complete cases; or (ii) all individuals. Three ODS analytical methods were considered.

Results: When longitudinal data are MNAR, ODS methods exhibit bias similar to that seen in random sampling. MNAR and MAR bias is exacerbated when sampling only participants with complete follow-up. Simulations indicate that ODS analyses that include participants with incomplete follow-up are robust to MCAR and less biased by MAR missingness.

Conclusion: Dropout is common in longitudinal cohort studies. Investigators utilizing ODS methods must consider the effect of dropout in both the retrospective sampling design and analysis.