The Causes of Rapid Infant Mortality Decline in England and Wales, 1861–1921. Part II

Ri, Woods; Pa, Watterson; Woodward, JH.

doi:10.1080/0032472031000143876

Cited by 157 publications

(66 citation statements)

References 2 publications

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“…This is because only a fraction of cases result in death. In addition, the reduced notifications in 1922 -1932 reflect the decline in measles mortality risk that characterized the first half of the twentieth century, and has been noted for other infectious diseases (see Brincker 1938;Woods et al 1988Woods et al , 1989Hardy 1993;Cliff et al 1998). While there is no consensus on the causes of this decline among demographers and medical historians, it is usually attributed to improvements in sanitation, access to clean water, housing, nutrition and healthcare practices (Hull 1988;Hardy 1993;Cliff et al 1998).…”

Section: The Datamentioning

confidence: 99%

Decreasing stochasticity through enhanced seasonality in measles epidemics

Mantilla-Beniers

Bjørnstad

Grenfell

et al. 2009

J. R. Soc. Interface.

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Seasonal changes in the environment are known to be important drivers of population dynamics, giving rise to sustained population cycles. However, it is often difficult to measure the strength and shape of seasonal forces affecting populations. In recent years, statistical time-series methods have been applied to the incidence records of childhood infectious diseases in an attempt to estimate seasonal variation in transmission rates, as driven by the pattern of school terms. In turn, school-term forcing was used to show how susceptible influx rates affect the interepidemic period. In this paper, we document the response of measles dynamics to distinct shifts in the parameter regime using previously unexplored records of measles mortality from the early decades of the twentieth century. We describe temporal patterns of measles epidemics using spectral analysis techniques, and point out a marked decrease in birth rates over time. Changes in host demography alone do not, however, suffice to explain epidemiological transitions. By fitting the time-series susceptible-infected-recovered model to measles mortality data, we obtain estimates of seasonal transmission in different eras, and find that seasonality increased over time. This analysis supports theoretical work linking complex population dynamics and the balance between stochastic and deterministic forces as determined by the strength of seasonality.

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Section: The Datamentioning

confidence: 99%

Decreasing stochasticity through enhanced seasonality in measles epidemics

Mantilla-Beniers

Bjørnstad

Grenfell

et al. 2009

J. R. Soc. Interface.

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“…These values correspond to a 1.5% decline at younger ages and mortality improvement of one percent at older ages. The decline at younger ages in several European countries occurred at an even faster rate (Woods et al, 1988 and1989), and the rate of one percent is below the current average mortality decline in the West. Figure 1 shows the period and cohort life expectancies for the Siler mortality change model in equation (5) At time zero, the period and cohort life expectancies are 38.5 and 42.4, respectively.…”

Section: Period and Cohort Models Of Mortalitymentioning

confidence: 99%

Age-specific contributions to changes in the period and cohort life expectancy

Canudas-Romo¹,

Schoen²

2005

DemRes

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“…British scholarship has focussed on describing and interpreting the urban infant mortality rate (IMR), with occasional forays into the nature of urban-rural differences (Woods, Watterson, and Woodward 1989;Lee 1991;Williams and Galley 1995). Nor have other countries, with the exception of Sweden (Brandström, Edvinsson, and Rogers 2000;Edvinsso, Garðarsdóttir, and Thorvaldsen 2008;Bengtsson and Dribe 2010), been examined more thoroughly.…”

Section: Introductionmentioning

confidence: 99%

“…For comparison, using an arbitrary population density of 100 persons per square kilometre, Woods, Watterson, and Woodward (1989) produced a set of 320 rural RDs. We note that analysis at RD level does not fully escape the problem of non-homogeneity noted earlier in relation to counties (all rural RDs had at least one town, sometimes quite large), but for a study of a whole country the RD is a good compromise between accuracy and complexity.…”

Section: Introductionmentioning

confidence: 99%