A missing dimension in measures of vaccination impacts

Immunological protection, acquired from either natural infection or vaccination, varies among hosts, reflecting underlying biological variation and affecting population-level protection. Owing to the nature of resistance mechanisms, distributions of susceptibility and protection entangle with pathogen dose in a way that can be decoupled by adequately representing the dose dimension. Any infectious processes must depend in some fashion on dose, and empirical evidence exists for an effect of exposure dose on the probability of transmission to mumps-vaccinated hosts [1], the case-fatality ratio of measles [2], and the probability of infection and, given infection, of symptoms in cholera [3]. Extreme distributions of vaccine protection have been termed leaky (partially protects all hosts) and all-or-nothing (totally protects a proportion of hosts) [4]. These distributions can be distinguished in vaccine field trials from the time dependence of infections [5]. Frailty mixing models have also been proposed to estimate the distribution of protection from time to event data [6], [7], although the results are not comparable across regions unless there is explicit control for baseline transmission [8]. Distributions of host susceptibility and acquired protection can be estimated from dose-response data generated under controlled experimental conditions [9]–[11] and natural settings [12], [13]. These distributions can guide research on mechanisms of protection, as well as enable model validity across the entire range of transmission intensities. We argue for a shift to a dose-dimension paradigm in infectious disease science and community health

One Is Enough: In Vivo Effective Population Size Is Dose-Dependent for a Plant RNA Virus

Effective population size (Ne) determines the strength of genetic drift and the frequency of co-infection by multiple genotypes, making it a key factor in viral evolution. Experimental estimates of Ne for different plant viruses have, however, rendered diverging results. The independent action hypothesis (IAH) states that each virion has a probability of infection, and that virions act independent of one another during the infection process. A corollary of IAH is that Ne must be dose dependent. A test of IAH for a plant virus has not been reported yet. Here we perform a test of an IAH infection model using a plant RNA virus, Tobacco etch virus (TEV) variants carrying GFP or mCherry fluorescent markers, in Nicotiana tabacum and Capsicum annuum plants. The number of primary infection foci increased linearly with dose, and was similar to a Poisson distribution. At high doses, primary infection foci containing both genotypes were found at a low frequency (<2%). The probability that a genotype that infected the inoculated leaf would systemically infect that plant was near 1, although in a few rare cases genotypes could be trapped in the inoculated leaf by being physically surrounded by the other genotype. The frequency of mixed-genotype infection could be predicted from the mean number of primary infection foci using the independent-action model. Independent action appears to hold for TEV, and Ne is therefore dose-dependent for this plant RNA virus. The mean number of virions causing systemic infection can be very small, and approaches 1 at low doses. Dose-dependency in TEV suggests that comparison of Ne estimates for different viruses are not very meaningful unless dose effects are taken into consideration

Quantification of diarrhea risk related to wastewater contact in Thailand

Wastewater reuse contributes to closing the nutrient recycling loop as a sustainable way of managing water resources. Bangkok has over a thousand man-made drainage and irrigation canals for such purposes. Its use for agricultural and recreational purposes has a long tradition in rural and peri-urban areas. However, the continuation of these practices is increasingly questioned since potential health risks are an issue if such practices are not appropriately managed. The microbial and chemical quality of canal water has considerably deteriorated over the last decade, mainly because of discharged, untreated domestic and industrial wastewater. It is important to understand the health risks of wastewater reuse and identify risky behaviors from the most highly exposed actors promote the safe use of wastewater. This study assessed diarrhea infection risks caused by the use of and contact with wastewater in Klong Luang municipality, a peri-urban setting in Northern Bangkok, using quantitative microbial risk assessment. Wastewater samples were collected from canals, sewers at household level, and vegetables grown in the canals for consumption. Samples were also collected from irrigation water from the agricultural fields. Two protozoa, Giardia lamblia and Entamoeba histolytica, were quantified and analyzed by real-time PCR, exposure assessment was conducted, and finally, the risk of infection due to contact with wastewater in different scenarios was calculated. The results showed that canal water and vegetables were heavily contaminated with G. lamblia and E. histolytica. Infection risk was high in tested scenarios and largely exceeded the acceptable risk given by WHO guideline