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. 2011 Nov 7;8(64):1584-93.
doi: 10.1098/rsif.2011.0062. Epub 2011 Apr 20.

Influence of birth rates and transmission rates on the global seasonality of rotavirus incidence

Affiliations

Influence of birth rates and transmission rates on the global seasonality of rotavirus incidence

Virginia E Pitzer et al. J R Soc Interface. .

Abstract

Rotavirus is a major cause of mortality in developing countries, and yet the dynamics of rotavirus in such settings are poorly understood. Rotavirus is typically less seasonal in the tropics, although recent observational studies have challenged the universality of this pattern. While numerous studies have examined the association between environmental factors and rotavirus incidence, here we explore the role of intrinsic factors. By fitting a mathematical model of rotavirus transmission dynamics to published age distributions of cases from 15 countries, we obtain estimates of local transmission rates. Model-predicted patterns of seasonal incidence based solely on differences in birth rates and transmission rates are significantly correlated with those observed (Spearman's ρ = 0.65, p < 0.05). We then examine seasonal patterns of rotavirus predicted across a range of different birth rates and transmission rates and explore how vaccination may impact these patterns. Our results suggest that the relative lack of rotavirus seasonality observed in many tropical countries may be due to the high birth rates and transmission rates typical of developing countries rather than being driven primarily by environmental conditions. While vaccination is expected to decrease the overall burden of disease, it may increase the degree of seasonal variation in the incidence of rotavirus in some settings.

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Figures

Figure 1.
Figure 1.
Fit of the model to age distributions of cases from 15 countries. The observed proportion of reported cases in the zero to five month, six to 11 month, 1, 2, 3 and 4 year old age groups are represented by the black bars, while the white bars are those predicted by the model. Developed countries are in the top line, while developing countries are in the bottom two lines. Within these groups, countries are ordered by distance from the equator (greatest to least); temperate countries are in the shaded region.
Figure 2.
Figure 2.
Predicted seasonal patterns of rotavirus incidence across a range of birth rates and transmission rates. The degree of seasonal fluctuation in incidence of rotavirus diarrhoea predicted by the model is indicated by the colour bar. The larger red–yellow region corresponds to strong annual epidemics, while the smaller red region in the lower left-hand corner corresponds to biennial epidemics. The estimated position for each of the 15 countries is plotted according to the symbols; note the estimated R0 for Malawi was greater than 100, but there was not much variation in the predicted seasonal pattern for this parameter region.
Figure 3.
Figure 3.
Predicted effect of vaccination on the seasonal incidence of rotavirus diarrhoea. (a) Relative size of peak seasonal incidence (as indicated by the colour bar) 5 years after vaccine introduction compared with peak incidence prior to vaccination for vaccine coverage levels of 50, 70 and 90 per cent of all infants at four months of age. (b,c) Weekly (blue lines) and average annual incidence (red lines) of severe rotavirus diarrhoea for a country with (b) CBR = 20 live births per 1000 and R0 = 35, and (c) CBR = 15 live births per 1000 and R0 = 25. Vaccination is introduced in year 3 at (i) 50%, (ii) 70% and (iii) 90% coverage.
Figure 4.
Figure 4.
Predicted age of first infection with rotavirus. Proportion of infants infected with rotavirus prior to 4 months of age (indicated by the colour bar) across a range of values for the CBR and transmission rate (R0) for the periods (a) prior to vaccine introduction, and (b) 10 years after vaccine introduction with 90% coverage.

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