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Yingcun Xia

Publications and source records attributed to Yingcun Xia.

2 recordsLinked to original sources

Cumulative effects of air pollution on public health.

Cumulative effect is an important way through which the pollutants affect public health. However, few existing dynamical models are well enough understood and documented to detect or quantify the cumulative effects and to answer pertinent questions posed by the World Health Organization (WHO): 'Is there a threshold below which no effects of the pollutants on health are expected to occur in all people?' and 'What averaging period (time pattern) is the most relevant from the point of view of health?'. Using a new semi-parametric time series modelling approach, which incorporates non-linearity and latent cumulative variables, we show that the cumulative effects on health due to continual exposure to environmental pollutants can be very serious even at levels below the national ambient air quality standards of America (NAAQS). The situation is especially worrying for chronic sufferers. Our study suggests that different pollutants may require different cumulative periods (on average) to impact on health but they share a similar functional form in respect of their impact. We also suggest some possible revision of the ambient air quality standards.

Air Pollution↗

Measles metapopulation dynamics: a gravity model for epidemiological coupling and dynamics.

Infectious diseases provide a particularly clear illustration of the spatiotemporal underpinnings of consumer-resource dynamics. The paradigm is provided by extremely contagious, acute, immunizing childhood infections. Partially synchronized, unstable oscillations are punctuated by local extinctions. This, in turn, can result in spatial differentiation in the timing of epidemics and, depending on the nature of spatial contagion, may result in traveling waves. Measles epidemics are one of a few systems documented well enough to reveal all of these properties and how they are affected by spatiotemporal variations in population structure and demography. On the basis of a gravity coupling model and a time series susceptible-infected-recovered (TSIR) model for local dynamics, we propose a metapopulation model for regional measles dynamics. The model can capture all the major spatiotemporal properties in prevaccination epidemics of measles in England and Wales.

Demography↗