Dataset Information

Comparative dynamics, seasonality in transmission, and predictability of childhood infections in Mexico.

ABSTRACT: The seasonality and periodicity of infections, and the mechanisms underlying observed dynamics, can have implications for control efforts. This is particularly true for acute childhood infections. Among these, the dynamics of measles is the best understood and has been extensively studied, most notably in the UK prior to the start of vaccination. Less is known about the dynamics of other childhood diseases, particularly outside Europe and the United States. In this paper, we leverage a unique dataset to examine the epidemiology of six childhood infections - measles, mumps, rubella, varicella, scarlet fever and pertussis - across 32 states in Mexico from 1985 to 2007. This dataset provides us with a spatio-temporal probe into the dynamics of six common childhood infections, and allows us to compare them in the same setting over the same time period. We examine three key epidemiological characteristics of these infections - the age profile of infections, spatio-temporal dynamics, and seasonality in transmission - and compare them with predictions from existing theory and past findings. Our analysis reveals interesting epidemiological differences between the six pathogens, and variations across space. We find signatures of term-time forcing (reduced transmission during the summer) for measles, mumps, rubella, varicella, and scarlet fever; for pertussis, a lack of term-time forcing could not be rejected.

SUBMITTER: Mahmud AS

PROVIDER: S-EPMC6020851 | biostudies-literature | 2017 Feb

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Comparative dynamics, seasonality in transmission, and predictability of childhood infections in Mexico.

Mahmud A S AS Metcalf C J E CJ Grenfell B T BT

Epidemiology and infection 20161122 3

The seasonality and periodicity of infections, and the mechanisms underlying observed dynamics, can have implications for control efforts. This is particularly true for acute childhood infections. Among these, the dynamics of measles is the best understood and has been extensively studied, most notably in the UK prior to the start of vaccination. Less is known about the dynamics of other childhood diseases, particularly outside Europe and the United States. In this paper, we leverage a unique da ...[more]

PMID: 27873563

Similar Datasets

Project description:Intestinal nematode infections affect a huge proportion of the world's population. Increasingly these infections, particularly amongst the poorest communities, are controlled through mass drug treatment programs. Seasonal variations of climate and behaviour in these regions can be significant, but their impact on the dynamics of infection and implications for the effectiveness of any mass drug treatment program (a pulsed reduction in worm burden in hosts) is not clearly understood. Here the effect of seasonality on the dynamics of the soil-based helminth, Ascaris lumbricoides, is investigated using a reformulated version of the Anderson-May model for macro-parasitic infections. Explicit analytical expressions are obtained for the stable oscillatory solution over the annual cycle, which provides a means of relating times of peak numbers of eggs, larvae and mature worms to seasonal variations. Numerical and analytical techniques are then used to consider the impact of seasonality on the optimal timing of drug treatment. Our results show that there is a relatively large window for the timing of optimal treatment, and the impact of repeated annual mass drug treatments can be substantially improved if they are timed to coincide with the months when the number of eggs and larvae are at their lowest - minimising reinfection. In terms of a more measurable quantity, in our example this corresponds to the months when the seasonal temperature is highest. Multiple annual treatments at (or close to) the optimal time each year are predicted to achieve local elimination in the community, whereas treatment at other times has a more limited impact. A key finding is that even for pronounced seasonality, perturbations in mean worm burden, and hence seasonal variation in observed egg output, may be small, potentially explaining why seasonal effects have been overlooked. Taken together these results suggest that seasonality of soil-transmitted helminths requires further experimental, field and mathematical study if the impact for mass drug administration programs is to be exploited.

Project description:BackgroundThe survival of coronaviruses are influenced by weather conditions and seasonal coronaviruses are more common in winter months. We examine the seasonality of respiratory infections in England and Wales and the associations between weather parameters and seasonal coronavirus cases.MethodsRespiratory virus disease data for England and Wales between 1989 and 2019 was extracted from the Second-Generation Surveillance System (SGSS) database used for routine surveillance. Seasonal coronaviruses from 2012 to 2019 were compared to daily average weather parameters for the period before the patient's specimen date with a range of lag periods.ResultsThe seasonal distribution of 985,524 viral infections in England and Wales (1989-2019) showed coronavirus infections had a similar seasonal distribution to influenza A and bocavirus, with a winter peak between weeks 2 to 8. Ninety percent of infections occurred where the daily mean ambient temperatures were below 10 °C; where daily average global radiation exceeded 500 kJ/m2/h; where sunshine was less than 5 h per day; or where relative humidity was above 80%. Coronavirus infections were significantly more common where daily average global radiation was under 300 kJ/m2/h (OR 4.3; CI 3.9-4.6; p < 0.001); where average relative humidity was over 84% (OR 1.9; CI 3.9-4.6; p < 0.001); where average air temperature was below 10 °C (OR 6.7; CI 6.1-7.3; p < 0.001) or where sunshine was below 4 h (OR 2.4; CI 2.2-2.6; p < 0.001) when compared to the distribution of weather values for the same time period. Seasonal coronavirus infections in children under 3 years old were more frequent at the start of an annual epidemic than at the end, suggesting that the size of the susceptible child population may be important in the annual cycle.ConclusionsThe dynamics of seasonal coronaviruses reflect immunological, weather, social and travel drivers of infection. Evidence from studies on different coronaviruses suggest that low temperature and low radiation/sunlight favour survival. This implies a seasonal increase in SARS-CoV-2 may occur in the UK and countries with a similar climate as a result of an increase in the R0 associated with reduced temperatures and solar radiation. Increased measures to reduce transmission will need to be introduced in winter months for COVID-19.

Dataset Information

Comparative dynamics, seasonality in transmission, and predictability of childhood infections in Mexico.

Publications

Comparative dynamics, seasonality in transmission, and predictability of childhood infections in Mexico.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets