Conserved patterns of incomplete reporting in pre-vaccine era childhood diseases

Gunning, Christian E.; Erhardt, Erik B.; Wearing, Helen J.

doi:10.1098/rspb.2014.0886

Cited by 8 publications

(20 citation statements)

References 39 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Summary statistics and observation counts are shown in Table 2. Overall, the average 6 reporting probability of pertussis is much lower than for measles, with a higher coefficient of variation among cities, as discussed in Gunning et al [24]. Figure 1 shows P obs , P est , and P c (rows) versus N and N m (columns).…”

Section: Resultsmentioning

confidence: 79%

“…As discussed in Gunning et al [24], no strong evidence of time-variable reporting is apparent in this system over the period of record, and reporting probability is assumed to be constant over time.…”

Section: Incomplete Observationmentioning

confidence: 99%

“…Thus, each city's r can be estimated from the ratio total case reports to total surviving births, summed over the period of observation: r = C obs / births. As described in Gunning et al [24], total surviving births are estimated from yearly per capita state birth rates and infant mortality rates, along with yearly city populations. We also estimate approximate confidence intervals on r by bootstrapping (yearly) birth and infant mortality rates.…”

Section: Incomplete Observationmentioning

confidence: 99%

“…First, bootstrap draws of r (henceforth r b ) were taken via non-parametric resampling. For each draw, yearly state birth rates and national infant mortality rates were resampled, and total births thus summed (see Gunning et al [24] for details). The resulting r b were used to compute N m from N , and a B-GLM was fit to the result.…”

Section: Estimating Uncertaintymentioning

confidence: 99%

“…In addition, reports of pertussis in adults was generally absent in the pre-vaccine era [18]. Consequently, pertussis reporting is generally less complete and more variable than measles reporting [22,24]. Such observational differences complicate meaningful comparisons between diseases, particularly in the presence of dynamical uncertainty.…”

mentioning

confidence: 99%

See 4 more Smart Citations

Evidence of cryptic incidence in childhood diseases

Gunning

Ferrari

Erhardt³

et al. 2016

Preprint

Self Cite

View full text Add to dashboard Cite

Persistence and extinction are key processes in infectious disease dynamics that, due to incomplete reporting, are seldom directly observable. For fully-immunizing diseases, reporting probabilities can be readily estimated from demographic records and case reports. Yet reporting probabilities are not sufficient to unambiguously reconstruct disease incidence from case reports. Here, we focus on disease presence (i.e., marginal probability of non-zero incidence), which provides an upper bound on the marginal probability of disease extinction. We examine measles and pertussis in pre-vaccine era U.S. cities, and describe a conserved scaling relationship between population size, reporting probability, and observed presence (i.e., non-zero case reports). We use this relationship to estimate disease presence given perfect reporting, and define cryptic presence as the difference between estimated and observed presence. We estimate that, in early 20 th century U.S. cities, pertussis presence was higher than measles presence across a range of population sizes, and that cryptic presence was common in small cities with imperfect reporting.While the methods employed here are specific to fully-immunizing diseases, our results suggest that cryptic incidence deserves careful attention, particularly in diseases with low case counts, poor reporting, and longer infectious periods.Recurrent epidemics are a common feature of these diseases, driven by long-term host demographics and periodic forcing of disease transmission via changes in host density, such as school terms [2][3][4] or economic migration [5,6]. At high incidence, susceptible hosts are rapidly depleted, leading to subsequent inter-epidemic troughs of low incidence, where stochastic extinction can occur. When infection is low or absent from a population, susceptible replenishment proceeds via the host demographic processes of birth and migration. These forces combine to yield characteristic yearly and multi-annual epidemic cycles in a range of diseases and human populations [7][8][9][10][11][12][13][14].The life histories of measles and pertussis differ significantly in pace: measles has a shorter life cycle, is more "invasive", and experiences more pronounced epidemics, while pertussis is the superior "colonizer". The slower life history of pertussis is expected to dampen the effects of isolation relative to measles, and is predicted to enhance dynamical stochasticity [15,16]. In pertussis, the contribution of waning immunity to observed dynamics has been a subject of extensive debate, both in infection-derived and vaccine-derived immunity [17][18][19]. In the pre-vaccine era, however, pertussis dynamics are consistent with the dynamics of infections that confer relatively long-lasting immunity, irrespective of whether the mechanism is long-term protection or natural immune boosting [20,21]. Reporting probabilities vary widely between these diseases, as well as between locations [3, 22-24]. Measlesinfection causes characteristic symptoms of fever, rash, and pathognomoni...

show abstract

Section: Resultsmentioning

confidence: 79%

Section: Incomplete Observationmentioning

confidence: 99%

Section: Incomplete Observationmentioning

confidence: 99%

Section: Estimating Uncertaintymentioning

confidence: 99%

mentioning

confidence: 99%

See 3 more Smart Citations

Evidence of cryptic incidence in childhood diseases

Gunning

Ferrari

Erhardt³

et al. 2016

Preprint

Self Cite

View full text Add to dashboard Cite

show abstract

Time Scales in Disease Transmission Dynamics

Andreasen

2023

Mathematics Online First Collections

View full text Add to dashboard Cite

The effects of demographic change on disease transmission and vaccine impact in a household structured population

et al. 2015

View full text Add to dashboard Cite

The demographic structure of populations in both more developed and less developed countries is changing: increases in life expectancy and declining fertility have led to older populations and smaller households. The implications of these demographic changes for the spread and control of infectious diseases are not fully understood. Here we use an individual based model with realistic and dynamic age and household structure to demonstrate the marked effect that demographic change has on disease transmission at the population and household level. The decline in fertility is associated with a decrease in disease incidence and an increase in the age of first infection, even in the absence of vaccination or other control measures. Although large households become rarer as fertility decreases, we show that there is a proportionate increase in incidence of disease in these households as the accumulation of susceptible clusters increases the potential for explosive outbreaks. By modelling vaccination, we provide a direct comparison of the relative importance of demographic change and vaccination on incidence of disease. We highlight the increased risks associated with unvaccinated households in a low fertility setting if vaccine behaviour is correlated with household membership. We suggest that models that do not account for future demographic change, and especially its effect on household structure, may potentially overestimate the impact of vaccination.

show abstract

Conserved patterns of incomplete reporting in pre-vaccine era childhood diseases

Cited by 8 publications

References 39 publications

Evidence of cryptic incidence in childhood diseases

Evidence of cryptic incidence in childhood diseases

Time Scales in Disease Transmission Dynamics

The effects of demographic change on disease transmission and vaccine impact in a household structured population

Contact Info

Product

Resources

About