Transmission routes of rare seasonal diseases: the case of norovirus infections

Pathogen transmission modes determine contact network structure, altering other pathogen characteristics

Pathogen traits can vary greatly and heavily impact the ability of a pathogen to persist in a population. Although this variation is fundamental to disease ecology, little is known about the evolutionary pressures that drive these differences, particularly where they interact with host behaviour. We hypothesized that host behaviours relevant to different transmission routes give rise to differences in contact network structure, constraining the space over which pathogen traits can evolve to maximize fitness. Our analysis of 232 contact networks across mammals, birds, reptiles, amphibians, arthropods, fish and molluscs found that contact network topology varies by contact type, most notably in networks that are representative of fluid-exchange transmission. Using infectious disease model simulations, we showed that these differences in network structure suggest pathogens transmitted through fluid-exchange contact types will need traits associated with high transmissibility to successfully proliferate, compared to pathogens that transmit through other types of contact. These findings were supported through a review of known traits of pathogens that transmit in humans. Our work demonstrates that contact network structure may drive the evolution of compensatory pathogen traits according to transmission strategy, providing essential context for understanding pathogen evolution and ecology.

The Impacts of Medical Resources on Emerging Self-Limiting Infectious Diseases

The spread of emerging self-limiting infectious diseases is closely related to medical resources. This paper introduces the concept of safe medical resources, i.e., the minimum medical resources that are needed to prevent the overburden of medical resources, and explores the impacts of medical resources on the spread of emerging self-limiting infectious diseases. The results showed that when the isolation rate of hospitalized patients who have mild infections is low, increasing the isolation rate of patients with severe infections requires safe more medical resources. On the contrary, when the isolation rate of hospitalized patients with mild infections is at a high level, increasing the isolation rate of patients with severe infections results in a decrease in safe medical resources. Furthermore, when the isolation rates of patients with mild and severe infections increase simultaneously, safe medical resources decrease gradually. That is to say, when the medical resources are at a low level, it is more necessary to improve the isolation rates of infected individuals so as to avoid the phenomenon of overburdened medical resources and control the spread of emerging infectious diseases. In addition, overwhelmed medical resources increase the number of deaths. Meanwhile, for different emerging self-limiting infectious diseases, as long as the recovery periods are the same, safe medical resources also remain the same.

Epidemiological and Genetic Characterization of Norovirus Outbreaks That Occurred in Catalonia, Spain, 2017–2019

Molecular characterization of human norovirus (HuNoV) genotypes enhances the understanding of viral features and illustrates distinctive evolutionary patterns. The aim of our study was to describe the prevalence of the genetic diversity and the epidemiology of the genotypes involved in HuNoV outbreaks in Catalonia (Spain) between 2017 and 2019. A total of 100 HuNoV outbreaks were notified with the predominance of GII (70%), followed by GI (27%) and mixed GI/GII (3%). Seasonality was observed for GII outbreaks only. The most prevalent genotypes identified were GII.4[P31] Sydney 2012, GII.4[P16] Sydney 2012 and GII.2[P16]. As compared to person-to-person (P/P) transmitted outbreaks, foodborne outbreaks showed significantly higher attack rates and lower duration. The average attack rate was higher in youth hostel/campgrounds compared to nursing homes. Only genotypes GI.4[P4], GII.2[P16], GII.4[P16], GII.4[P31] and GII.17[P17] were consistently detected every year, and only abundance of GII.2[P16] showed a negative trend over time. GII.4 Sydney 2012 outbreaks were significantly associated to nursing homes, while GII.2[P16] and GI.3[P3] were most frequently identified in youth hostel/campgrounds. The average attack rate was significantly higher when comparing GII.2[P16] vs. GI.4[P4], GII.2[P16] vs. GII.4[P31] Sydney 2012, and GII.6[P7] vs. GII.4[P31] Sydney 2012. No correlations were found between genotype and outbreak duration or age of affected individuals.

Using the SEIR model to constrain the role of contaminated fomites in spreading an epidemic: An application to COVID-19 in the UK

The use of the SEIR model of compartmentalized population dynamics with an added fomite term is analysed as a means of statistically quantifying the contribution of contaminated fomites to the spread of a viral epidemic. It is shown that for normally expected lifetimes of a virus on fomites, the dynamics of the populations are nearly indistinguishable from the case without fomites. With additional information, such as the change in social contacts following a lockdown, however, it is shown that, under the assumption that the reproduction number for direct infection is proportional to the number of social contacts, the population dynamics may be used to place meaningful statistical constraints on the role of fomites that are not affected by the lockdown. The case of the Spring 2020 UK lockdown in response to COVID-19 is presented as an illustration. An upper limit is found on the transmission rate by contaminated fomites of fewer than 1 in 30 per day per infectious person (95% CL) when social contact information is taken into account. Applied to postal deliveries and food packaging, the upper limit on the contaminated fomite transmission rate corresponds to a probability below 1 in 70 (95% CL) that a contaminated fomite transmits the infection. The method presented here may be helpful for guiding health policy over the contribution of some fomites to the spread of infection in other epidemics until more complete risk assessments based on mechanistic modelling or epidemiological investigations may be completed.

Impact of Nonpharmaceutical Interventions for Severe Acute Respiratory Syndrome Coronavirus 2 on Norovirus Outbreaks: An Analysis of Outbreaks Reported By 9 US States

In April 2020, the incidence of norovirus outbreaks reported to the National Outbreak Reporting System (NORS) dramatically declined. We used regression models to determine if this decline was best explained by underreporting, seasonal trends, or reduced exposure due to non-pharmaceutical interventions (NPIs) implemented for SARS-CoV-2 using data from 9 states from July 2012–July 2020. The decline in norovirus outbreaks was significant for all 9 states and underreporting or seasonality are unlikely to be the primary explanations for these findings. These patterns were similar across a variety of settings. NPIs appear to have reduced incidence of norovirus, a non-respiratory pathogen.

Long-term dynamics of Norovirus transmission in Japan, 2005-2019

Norovirus continues to evolve, adjusting its pathogenesis and transmissibility. In the present study, we systematically collected datasets on Norovirus outbreaks in Japan from 2005 to 2019 and analyzed time-dependent changes in the asymptomatic ratio, the probability of virus detection, and the probability of infection given exposure. Reports of 1,728 outbreaks were published, and feces from all involved individuals, including those with asymptomatic infection, were tested for virus in 434 outbreaks. We found that the outbreak size did not markedly change over this period, but the variance in outbreak size increased during the winter (November–April). Assuming that natural history parameters did not vary over time, the asymptomatic ratio, the probability of virus detection, and the probability of infection given exposure were estimated to be 18.6%, 63.3% and 84.5%, respectively. However, a model with time-varying natural history parameters yielded better goodness-of-fit and suggested that the asymptomatic ratio varied by year. The asymptomatic ratio was as high as 25.8% for outbreaks caused by genotype GII.4 noroviruses. We conclude that Norovirus transmissibility has not changed markedly since 2005, and that yearly variation in the asymptomatic ratio could potentially be explained by the circulating dominant genotype.

Impact of Nonpharmaceutical Interventions for Severe Acute Respiratory Syndrome Coronavirus 2 on Norovirus Outbreaks: An Analysis of Outbreaks Reported By 9 US States

In April 2020, the incidence of norovirus outbreaks reported to the National Outbreak Reporting System dramatically declined. We used regression models to determine if this decline was best explained by underreporting, seasonal trends, or reduced exposure due to nonpharmaceutical interventions (NPIs) implemented for severe acute respiratory syndrome coronavirus 2 using data from 9 states from July 2012 to July 2020. The decline in norovirus outbreaks was significant for all 9 states, and underreporting and/or seasonality are unlikely to be the primary explanation for these findings. These patterns were similar across a variety of settings. NPIs appear to have reduced incidence of norovirus, a nonrespiratory pathogen.

Preface to theme issue 'Modelling infectious disease outbreaks in humans, animals and plants: epidemic forecasting and control'

This preface forms part of the theme issue 'Modelling infectious disease outbreaks in humans, animals and plants: epidemic forecasting and control'. This theme issue is linked with the earlier issue 'Modelling infectious disease outbreaks in humans, animals and plants: approaches and important themes'.

Detection, forecasting and control of infectious disease epidemics: modelling outbreaks in humans, animals and plants

The 1918 influenza pandemic is one of the most devastating infectious disease epidemics on record, having caused approximately 50 million deaths worldwide. Control measures, including prohibiting non-essential gatherings as well as closing cinemas and music halls, were applied with varying success and limited knowledge of transmission dynamics. One hundred years later, following developments in the field of mathematical epidemiology, models are increasingly used to guide decision-making and devise appropriate interventions that mitigate the impacts of epidemics. Epidemiological models have been used as decision-making tools during outbreaks in human, animal and plant populations. However, as the subject has developed, human, animal and plant disease modelling have diverged. Approaches have been developed independently for pathogens of each host type, often despite similarities between the models used in these complementary fields. With the increased importance of a One Health approach that unifies human, animal and plant health, we argue that more inter-disciplinary collaboration would enhance each of the related disciplines. This pair of theme issues presents research articles written by human, animal and plant disease modellers. In this introductory article, we compare the questions pertinent to, and approaches used by, epidemiological modellers of human, animal and plant pathogens, and summarize the articles in these theme issues. We encourage future collaboration that transcends disciplinary boundaries and links the closely related areas of human, animal and plant disease epidemic modelling. This article is part of the theme issue 'Modelling infectious disease outbreaks in humans, animals and plants: approaches and important themes'. This issue is linked with the subsequent theme issue 'Modelling infectious disease outbreaks in humans, animals and plants: epidemic forecasting and control'.