To estimate the impacts of demographic factors and income disparities on the case fatality rate (CFR) of COVID-19 in Hong Kong, taking into account the influence of reporting delays (ie, the duration between symptom onset and case confirmation).

Retrospective observational longitudinal study.

A total of 7406 symptomatic patients with residence information reported between 23 January 2020 and 2 October 2021.

The study examined the disparity in COVID-19 deaths associated with the factors such as age (≥65 vs 0–64 years old groups), gender and the income level of districts (low income vs non-low income). The severe reporting delay (>10 days) was considered as the mediator for mediation analysis. A Cox proportional hazards regression model was constructed.

We found that CFR was 3.07% in the low-income region, twofold higher than 1.34% in the other regions. Although the severe reporting delay was associated with a hazard ratio (HR) of about 1.9, its mediation effect was only weakly present for age, but not for gender or income level. Hence, high CFR in Hong Kong was largely attributed to the direct effects of the elderly (HR 25.967; 95% CI 14.254 to 47.306) and low income (HR 1.558; 95% CI 1.122 to 2.164).

The disparity in COVID-19 deaths between income regions is not due to reporting delays, but rather to health inequities in Hong Kong. These risks may persist after the discontinuation of test-and-trace measures and extend to other high-threat respiratory pathogens. Urgent actions are required to identify vulnerable groups in low-income regions and understand the underlying causes of health inequities.

The objective of this study was to explore determinants of variation in overall caretaker satisfaction with curative care for sick children under the age of 5 in five low-income and middle-income countries.

A pooled cross-sectional analysis was conducted using data from the Service Provision Assessment.

We used data collected in five countries (Afghanistan, Democratic Republic of the Congo, Haiti, Malawi and Tanzania) between 2013 and 2018.

Respondents were 13 149 caretakers of children under the age of 5 who consulted for a sick child visit.

The outcome variable was whether the child’s caretaker was very satisfied versus more or less satisfied or not satisfied overall. Predictors pertained to child and caretaker characteristics, health system foundations and process of care (eg, care competence, user experience). Two-level logistic regression models were used to assess the extent to which these categories of variables explained variation in satisfaction. The main analyses used pooled data; country-level analyses were also performed.

Process of care, including user experience, explained the largest proportion of variance in caretaker satisfaction (13.8%), compared with child and caretaker characteristics (0.9%) and health system foundations (3.8%). The odds of being very satisfied were lower for caretakers who were not given adequate explanation (OR: 0.56, 95% CI 0.46 to 0.67), who had a problem with medication availability (OR: 0.31, 95% CI 0.27 to 0.35) or who encountered a problem with the cost of services (OR: 0.57, 95% CI 0.48 to 0.66). The final model explained only 21.8% of the total variance. Country-level analyses showed differences in variance explained and in associations with predictors.

Better process of care, especially user experience, should be prioritised for its benefit regarding caretaker satisfaction. Unmeasured factors explained the majority of variation in caretaker satisfaction and should be explored in future studies.