Demographic and Health Indicators in Correlation to Interstate Variability of Incidence, Confirmation, Hospitalization, and Lethality in Mexico: Preliminary Analysis from Imported and Community Acquired Cases during COVID-19 Outbreak

Abstract

This study’s objective is to analyze the incidence, lethality, hospitalization, and confirmation of COVID-19 cases in Mexico. Sentinel surveillance for COVID-19 cases in Mexico began after the confirmation of the first patient with community transmission. Methods: This epidemiologic, cross-sectional study includes all clinically suspected, and laboratory-confirmed cases nationwide from the beginning of the outbreak to 21 April 2020. State-cluster demographic data and health indicators were analyzed in reference to epidemiologic measures, with logistic regressions for the dependent variables of incidence, confirmation, and lethality. Results: The national incidence was 13.89/100,000 inhabitants with a 6.52% overall lethality and a confirmed-case mortality of 11.1%. The incidence variation significantly correlated with migration, but not urbanization. Pediatric patients were less prone to be tested (OR = −3.92), while geriatric individuals were a priority. State lethality positively correlated with the proportion of the population assisted at public hospitals and correlated inversely to the number of hospitals and clinics in the state. Conclusions: Migration strongly correlated with incidence; elderly patients had lower odds of being hospitalized but were likely to die. Patients aged <15 were less prone to be laboratory-confirmed. Case confirmation was not performed in all hospitalized patients, but 72.15% of hospitalized patients had favorable outcomes to date.

Temporal analysis of the clinical evolution of confirmed cases of COVID-19 in the state of Mato Grosso do Sul - Brazil

“…Although the incidence of cases was higher in the macro-region of Dourados, the largest proportion of deaths occurred in the region of Corumbá, which had a mortality rate of 2.58% and a statistically significant relationship among the regions. This index exceeded the calculated estimate for COVID-19 in China, where the mortality rate was 1.4% 27 , but was lower than the overall mortality rate of 6.52% in Mexico 28 . There are still many uncertainties and unknowns in relation to the viral mortality of COVID-19, since it is related to other factors 29 .…”

SARS-CoV-2 among migrants and forcibly displaced populations: a rapid systematic review

“…[17] An ecological study investigating migrants in transit in Mexico found a higher Incidence Risk Ratio (IRR: 6·43, 95%CI, 4·41-9·39) for SARS-CoV-2 in state cluster populations with a higher proportion of migrants. [25] Contextual factors, such as dormitories, were associated with incidence risks in migrant workers in the range of 5·64% (95%CI, 5·56-5·72) to 19·43% (95%CI, 18·75-20·12)[18] and 21·15% (95%CI, 20·12-22·21)[19].…”

“…[16] In contrast, the odds of interstate migrants was 1·36 (95%CI, 1·19-1·54) times the odds of hospitalisation than the reference (Mexican) population. [25] About 6·49% of all hospitalised SARS-CoV-2 cases in Mexico from 28th February until 21st April 2020 were interstate migrants. [25] However, the IRR for hospitalisation in state cluster populations with a higher proportion of migrants showed an inverse association (IRR: 0·65, 95%CI 0·58-0·74).…”

“…[22] Non-modelling studies report a mortality rate among interstate migrants of 4·75% (95%CI, 4·06-5·43) with an odds ratio for fatal outcomes of 2·01 (95%CI, 1·46-2·76) compared to average state-cluster characteristics. [25] The IRR for lethality in state-clusters with higher proportions of migrants (IRR: 1·02, 95%CI, 0·98-1·02) showed a mild tendency to be higher in these populations. [25] Guijarro et al investigate SARS-CoV-2 cases at a hospital in Alcorcón, Spain, finding 33% of severe cases in migrants (defined by country of origin) compared to 63% in the Spanish population.…”

Modeling the incidence and death rates of COVID-19 pandemic in different regions of the world

“…However, for many other authors, the epidemic has the potential to have a major impact on these populations, considering poverty, the greater agglomeration, as well as the poor conditions of health services (Lumu 2020;Ongole et al 2020;Osseni 2020). Countries in North America region presents the larger MRC, perhaps partly explained by the high population density and differences in age and racial structures of countries in that region with the greatest weight in Mexico and United States (Holmes et al 2020;Mendez-Dominguez et al 2020) while the CFR show more variability among the 11 regions with larger values for the countries in North Africa region, certainly largely due to poor health service structures in the countries of that region, with little capacity to deal with good response to critically ill patients, due to the lack of ICU beds and trained medical personnel (Ohia et al, 2020). Table 1 presents summary statistics (means, standard-deviations, minimum and maximum for the IR, MRC and CFR for each region (Asia Middle East; Central America; Central Asia; Caribbean; East Asia; Europe; North Africa; North America; Oceania; South America; Sub Saharan Africa).…”