Geospatial Variability in Excess Death Rates during the COVID-19 Pandemic in Mexico: Examining Socio Demographic and Population Health Characteristics

Background: Mexico has suffered one of the highest COVID-19 mortality rates in the world. In this study we examined how socio-demographic and population health characteristics shape the geospatial variability in excess mortality patterns during the COVID-19 pandemic in Mexico. Methods: Weekly all-cause mortality time series for all 32 Mexican states, from January 4, 2015 to April 10, 2021, were analyzed to estimate the excess mortality rates using Serfling regression models. The association between socio-demographic, health indicators and excess mortality rates were determined using multiple linear regression analyses. Finally, we used functional data analysis to characterize clusters of states with distinct mortality growth rate curves. Results: The overall all-cause excess deaths rate during the COVID-19 pandemic in Mexico until April 10, 2021 was estimated at 39.66 per 10 000 population. The lowest excess death rates were observed in southeastern states including Chiapas (12.72), Oaxaca (13.42) and Quintana Roo (19.41) whereas Mexico City had the highest excess death rate (106.17), followed by Tlaxcala (51.99) and Morelos (45.90). We found a positive association of excess mortality rates with aging index (P value<.0001), marginalization index (P value<.0001), and average household size (P value=0.0003) in the final adjusted model (Model R2=76%). We identified four distinct clusters with qualitatively similar excess mortality curves. Conclusion: Central states exhibited the highest excess mortality rates whereas the distribution of aging index, marginalization index, and average household size explained the variability in excess mortality rates across Mexico. Our findings can help tailor interventions to mitigate the mortality impact of the pandemic.

ASSESSMENT OF RURAL HOUSEHOLDS FOOD INSECURITY DURING COVID-19 PANDEMIC IN SOUTH-EAST NIGERIA

The problem of food insecurity remains a challenge in developing countries, especially in rural areas. Despite the rising level of food insecurity, COVID-19 set in and was said to pose a threat to food security globally if adequate measures are not quickly put in place. This study, therefore, described the socio-economic characteristics of the respondents; examined the extent to which the rural households are food secure or otherwise during the COVID-19 pandemic and examine the drivers of food security status among rural households in South-East Nigeria. Primary data were collected from 200 households with the use of structured questionnaires. Data were analysed using descriptive statistics, food security index and logistics regression. Results of the findings revealed that the majority of the household heads were male (92%), married (93.5%), educated (87.5%) and had an average age of 54 years. They had an average household size of 7 persons, an average farming experience of 22 years, an average monthly income of N14, 305.5 and majority (83%) do not belong to a cooperative society. Majority (69.5%) of the households were food insecure, while only (30.5%) were food secure. The food-secure households had an average household size of 5 persons, while the food insecure households had 9 persons in their households. The headcount ratio of food secure households was 0.30, while it was 0.70 for food-insecure households. This shows that at least two out of three persons were food insecure in the study area. The surplus/shortfall index indicates that the food secure households exceeded the calorie requirement by 12%, while the food insecure fell short of the recommended calorie intake by 39%. Square food insecure gap or square shortfall index which indicate the severity of food insecurity among the food insecure household was 0.0056. The average calorie available (adult equivalent per day) for food secure households was 2523.5kcal, while average calorie available (AE/day) for food-insecure households was 1389.05kcal. The identified positive drivers of food security were marital status, educational level, cooperative members and annual income of the household heads. While, age of household head, household size and COVID-19 negatively influenced food security status. The study recommends, among others, putting in place immediate policy measures to reduce the effect of COVID-19 pandemic on rural household’s food security through the provision of enough palliatives which should be monitored so that it gets to the targeted population. Effective household size management and enlightenment programs on modern family planning techniques should be encouraged in rural areas. Rural households should also be educated on the nutritional implication of the various food items such as egg, milk, soybean and fish, especially for children to increase their protein intake and boost their immune system against COVID-19.

Modifying SEIR models to explore the role of average household size in the era of lockdowns and social distancing

Compartmental models have long been used to study the dynamics of infectious diseases without requiring the intensive computational power of more detailed simulations. The well mixing assumption on which they are based is typically valid when people are meeting a significant number of other people each day. However, in the Covid-19 era of lockdowns and social distancing, the number of non-household contacts has dropped significantly. Standard SEIR models cannot produce the expected result of an idealised lockdown (i.e. no non-household contacts), where the final number of infected is less than the average household size times the number of infected and exposed at the time of the lockdown. To correct this anomaly, we separate the household and non-household contributions to the total cases and apply a carrying capacity to the household acquired cases. Finally, we illustrate the application of the model to two countries with completely different approaches to managing the SARS-CoV-2 pandemic, New Zealand and Sweden. The sharp drop in cases in New Zealand following their lockdown can be well explained with a carrying capacity model, while we show that the Swedish approach could be extremely risky for countries with higher average household sizes.

An Analysis of COVID-19 Mortality at the Local Authority Level in England

This study analyses COVID-19 mortality at the local authority level in England. The dependent variable is the age-standardised COVID-19 mortality rate. Two separate analyses are reported: one using untransformed variables, and one using logged variables (where appropriate). In the former, five variables explain 73% of the variance in COVID-19 mortality rate: cumulative confirmed cases rate, population density, % black or Asian, average household size, and a deprivation index. In the latter, four variables explain 72% of the variance in log COVID-19 mortality rate: log cumulative confirmed cases rate, log % black or Asian, average household size, and the deprivation index. (A health index does not reach statistical significance in either analysis, most likely because it is somewhat crude and the dependent variable is age-standardised.) Cumulative confirmed cases rate, average household size and % black or Asian are the strongest and most consistent predictors of COVID-19 mortality.

An ecological analysis of pertussis disease in Minnesota, 2009–2013

SUMMARYThe increase in pertussis cases in Minnesota in the last decade has been mainly attributed to the switch from whole cell to acellular pertussis [as part of the diphtheria, tetanus and acellular pertussis vaccine (DTaP)]. It is unclear, however, to what degree community-level risk factors also contribute. Understanding these factors can help inform public health policy-makers about where else to target resources. We performed an ecological analysis within Minnesota to identify risk factors at the county level using a Bayesian Poisson generalized linear areal model to account for spatial dependence. Univariate analyses suggested an association between increased pertussis rates at the county level and white maternal ethnicity, being US born, urban counties and average household size. In the multivariable analysis, the rate of pertussis was 1·79 times greater for urbanvs.rural counties and 4·75 times greater for counties with a one-person larger average household size. Pertussis rates in counties with higher (i.e. 4+DTaP) receipt in children were 0·97 times lower. Examining county-level factors associated with varying levels of pertussis may help identify those counties that would most benefit from targeted interventions and increased resource allocation.

Urban Commuting and Daytime Population in Small Areas of a Metropolis:A Case Study of Brno, Czech Republic

A simplified modelling approach to urban commuting patterns is achieved by focusing on daytime populations rather than on commuters, or on the commuting process itself. Whereas past studies were usually economic in nature, and viewed commuting as a process within the continuum of urban space and time, the approach addressing daytime populations transforms the modelling attempt into a demographic deliberation of a binary situation where switching of values between daytime and night-time indicators in each subarea throughout a metropolis is considered. The present study shows that such a focus on diurnal change as a binary concept offers a new paradigm in conceptualizing metropolitan commuting and transportation. Under certain assumptions, rooted in recent observations of metropolitan areas elsewhere, this study conjectures an analytic function for the estimation of daytime populations in small areas throughout the metropolitan region of Brno, Czech Republic. The conjectured relationship is a logistic function that utilizes as its independent variable the average household size in each of the subareas throughout the metropolitan region. Based on the data from the Czech census of 2001, the distributions of average household size and of residential populations throughout the metropolitan region are applied in a case study illustrating the utility of the proposed approach for the estimation of daytime populations throughout the region. The iterative procedure advanced here offers considerable potential for further applications elsewhere. KEY WORDS: metropolitan commuting, urban transportation, Brno, daytime population, average household size, logistic function, small area demography