AIM: In Mexico, as in other societies, migrants are seen as over-users of health services. However, the extent, distribution, and trends of use over time are unknown. Evidence is needed to inform health policies and improve health services for foreign patients. The objective of this study was to examine factors associated with the distribution and trends of Mexican and foreign resident hospitalizations in Mexican public hospitals from 2010 to 2020. METHODS: A graphical and statistical analysis (descriptive and correlational) of discharge trends in public hospitals was carried out. Hospitalization trends were analyzed by country of habitual residence (Mexico, US, Central and South America, and Other Continents), age, sex, primary discharge category, and region of service delivery. Adjusted Poisson modeling was used to examine the factors associated with annual hospitalizations of Mexican and foreign residents. RESULTS: Between 2010 and 2020, there were 26,780,808 hospitalizations in Mexican public hospitals. Of these, 0.05% were of foreign residents. Hospitalizations for Mexican residents remained stable from 2010 to 2019, while those for foreign residents trended upward over the same period. In 2020, hospitalizations of Mexican residents fell by 36.6%, while foreign resident hospitalizations fell by 348.8%. The distribution of hospitalizations by sex was higher among females for all categories of habitual residence, except among US residents. Obstetric discharges were the most common reason for hospitalization among Mexican residents (42.45%), Central and South American residents (42.24%), and residents from Other Continents (13.73%). The average hospital stay was 2 days. Poisson regression confirmed these results, showing that hospitalizations was higher among women (except among foreign residents) and in the ≤ 17 age group. Poisson modeling also showed that trauma injury was the leading cause of discharge for foreign residents after obstetric causes. DISCUSSION: It is unlikely the upward trend in hospitalizations among foreign residents in Mexico from 2010 to 2019 affected the Mexican public health system, given the small proportion (0.05%) of hospitalizations and the brief length of hospital stay. The increased number of hospitalizations during the study period may be explained by local and national measures to facilitate foreign residents' access to hospital services, while the decrease in hospital utilization in 2020 is likely associated with COVID-19. Geographic location and the most frequent primary discharge categories of hospitalizations within each population could provide evidence for modifications to public health policy in Mexico.

OBJECTIVES: The COVID-19 pandemic has highlighted the importance and complexity of a country's ability to effectively respond. The Joint External Evaluation (JEE) assessment was launched in 2016 to assess a country's ability to prevent, detect and respond to public health emergencies. We examined whether JEE indicators could be used to predict a country's COVID-19 response performance to tailor a country's support more effectively. DESIGN: From April to August 2020, we conducted interviews with Centers for Disease Control and Prevention country offices that requested COVID-19 support and previously completed the JEE (version 1.0). We used an assessment tool, the 'Emergency Response Capacity Tool' (ERCT), to assess COVID-19 response performance. We analysed 28 ERCT indicators aligned with eight JEE indicators to assess concordance and discordance using strict agreement and weighted kappa statistics. Generalised estimating equation (GEE) models were used to generate predicted probabilities for ERCT scores using JEE scores as the independent model variable. RESULTS: Twenty-three countries met inclusion criteria. Of the 163 indicators analysed, 42.3% of JEE and ERCT scores were in agreement (p value=0.02). The JEE indicator with the highest agreement (62%) was 'Emergency Operations Center (EOC) operating procedures and plans', while the lowest (16%) was 'capacity to activate emergency operations'. Findings were consistent with weighted kappa statistics. In the GEE model, EOC operating procedures and plans had the highest predicted probability (0.86), while indicators concerning response strategy and coordination had the lowest (≤0.5). CONCLUSIONS: Overall, there was low agreement between JEE scores and COVID-19 response performance, with JEE scores often trending higher. JEE indicators concerning coordination and operations were least predictive of COVID-19 response performance, underscoring the importance of not inferring country response readiness from JEE scores alone. More in-depth country-specific investigations are likely needed to accurately estimate response capacity and tailor countries' global health security activities.