Epidemiological and health economic implications of symptom propagation in respiratory pathogens: A mathematical modelling investigation.

BACKGROUND: Respiratory pathogens inflict a substantial burden on public health and the economy. Although the severity of symptoms caused by these pathogens can vary from asymptomatic to fatal, the factors that determine symptom severity are not fully understood. Correlations in symptoms between infector-infectee pairs, for which evidence is accumulating, can generate large-scale clusters of severe infections that could be devastating to those most at risk, whilst also conceivably leading to chains of mild or asymptomatic infections that generate widespread immunity with minimal cost to public health. Although this effect could be harnessed to amplify the impact of interventions that reduce symptom severity, the mechanistic representation of symptom propagation within mathematical and health economic modelling of respiratory diseases is understudied. METHODS AND FINDINGS: We propose a novel framework for incorporating different levels of symptom propagation into models of infectious disease transmission via a single parameter, α. Varying α tunes the model from having no symptom propagation (α = 0, as typically assumed) to one where symptoms always propagate (α = 1). For parameters corresponding to three respiratory pathogens-seasonal influenza, pandemic influenza and SARS-CoV-2-we explored how symptom propagation impacted the relative epidemiological and health-economic performance of three interventions, conceptualised as vaccines with different actions: symptom-attenuating (labelled SA), infection-blocking (IB) and infection-blocking admitting only mild breakthrough infections (IB_MB). In the absence of interventions, with fixed underlying epidemiological parameters, stronger symptom propagation increased the proportion of cases that were severe. For SA and IB_MB, interventions were more effective at reducing prevalence (all infections and severe cases) for higher strengths of symptom propagation. For IB, symptom propagation had no impact on effectiveness, and for seasonal influenza this intervention type was more effective than SA at reducing severe infections for all strengths of symptom propagation. For pandemic influenza and SARS-CoV-2, at low intervention uptake, SA was more effective than IB for all levels of symptom propagation; for high uptake, SA only became more effective under strong symptom propagation. Health economic assessments found that, for SA-type interventions, the amount one could spend on control whilst maintaining a cost-effective intervention (termed threshold unit intervention cost) was very sensitive to the strength of symptom propagation. CONCLUSIONS: Overall, the preferred intervention type depended on the combination of the strength of symptom propagation and uptake. Given the importance of determining robust public health responses, we highlight the need to gather further data on symptom propagation, with our modelling framework acting as a template for future analysis.

Local infectious disease experience influences vaccine refusal rates: a natural experiment.

Vaccination has been critical to the decline in infectious disease prevalence in recent centuries. Nonetheless, vaccine refusal has increased in recent years, with complacency associated with reductions in disease prevalence highlighted as an important contributor. We exploit a natural experiment in Glasgow at the beginning of the twentieth century to investigate whether prior local experience of an infectious disease matters for vaccination decisions. Our study is based on smallpox surveillance data and administrative records of parental refusal to vaccinate their infants. We analyse variation between administrative units of Glasgow in cases and deaths from smallpox during two epidemics over the period 1900-1904, and vaccine refusal following its legalization in Scotland in 1907 after a long period of compulsory vaccination. We find that lower local disease incidence and mortality during the epidemics were associated with higher rates of subsequent vaccine refusal. This finding indicates that complacency influenced vaccination decisions in periods of higher infectious disease risk, responding to local prior experience of the relevant disease, and has not emerged solely in the context of the generally low levels of infectious disease risk of recent decades. These results suggest that vaccine delivery strategies may benefit from information on local variation in incidence.

Lumpy species coexistence arises robustly in fluctuating resource environments.

The effect of life-history traits on resource competition outcomes is well understood in the context of a constant resource supply. However, almost all natural systems are subject to fluctuations of resources driven by cyclical processes such as seasonality and tidal hydrology. To understand community composition, it is therefore imperative to study the impact of resource fluctuations on interspecies competition. We adapted a well-established resource-competition model to show that fluctuations in inflow concentrations of two limiting resources lead to the survival of species in clumps along the trait axis, consistent with observations of "lumpy coexistence" [Scheffer M, van Nes EH (2006) Proc Natl Acad Sci USA 103:6230-6235]. A complex dynamic pattern in the available ambient resources arose very early in the self-organization process and dictated the locations of clumps along the trait axis by creating niches that promoted the growth of species with specific traits. This dynamic pattern emerged as the combined result of fluctuations in the inflow of resources and their consumption by the most competitive species that accumulated the bulk of biomass early in assemblage organization. Clumps emerged robustly across a range of periodicities, phase differences, and amplitudes. Given the ubiquity in the real world of asynchronous fluctuations of limiting resources, our findings imply that assemblage organization in clumps should be a common feature in nature.

Towards the elimination of dog-mediated rabies: development and application of an evidence-based management tool.

BACKGROUND: International organizations advocate for the elimination of dog-mediated rabies, but there is only limited guidance on interpreting surveillance data for managing elimination programmes. With the regional programme in Latin America approaching elimination of dog-mediated rabies, we aimed to develop a tool to evaluate the programme's performance and generate locally-tailored rabies control programme management guidance to overcome remaining obstacles. METHODS: We developed and validated a robust algorithm to classify progress towards rabies elimination within sub-national administrative units, which we applied to surveillance data from Brazil and Mexico. The method combines criteria that are easy to understand, including logistic regression analysis of case detection time series, assessment of rabies virus variants, and of incursion risk. Subjecting the algorithm to robustness testing, we further employed simulated data sub-sampled at differing levels of case detection to assess the algorithm's performance and sensitivity to surveillance quality. RESULTS: Our tool demonstrated clear epidemiological transitions in Mexico and Brazil: most states progressed rapidly towards elimination, but a few regressed due to incursions and control lapses. In 2015, dog-mediated rabies continued to circulate in the poorest states, with foci remaining in only 1 of 32 states in Mexico, and 2 of 27 in Brazil, posing incursion risks to the wider region. The classification tool was robust in determining epidemiological status irrespective of most levels of surveillance quality. In endemic settings, surveillance would need to detect less than 2.5% of all circulating cases to result in misclassification, whereas in settings where incursions become the main source of cases the threshold detection level for correct classification should not be less than 5%. CONCLUSION: Our tool provides guidance on how to progress effectively towards elimination targets and tailor strategies to local epidemiological situations, while revealing insights into rabies dynamics. Post-campaign assessments of dog vaccination coverage in endemic states, and enhanced surveillance to verify and maintain freedom in states threatened by incursions were identified as priorities to catalyze progress towards elimination. Our finding suggests genomic surveillance should become increasingly valuable during the endgame for discriminating circulating variants and pinpointing sources of incursions.

Everything is not everywhere: can marine compartments shape phytoplankton assemblages?

The idea that 'everything is everywhere, but the environment selects' has been seminal in microbial biogeography, and marine phytoplankton is one of the prototypical groups used to illustrate this. The typical argument has been that phytoplankton is ubiquitous, but that distinct assemblages form under environmental selection. It is well established that phytoplankton assemblages vary considerably between coastal ecosystems. However, the relative roles of compartmentalization of regional seas and site-specific environmental conditions in shaping assemblage structures have not been specifically examined. We collected data from coastal embayments that fall within two different water compartments within the same regional sea and are characterized by highly localized environmental pressures. We used principal coordinates of neighbour matrices (PCNM) and asymmetric eigenvector maps (AEM) models to partition the effects that spatial structures, environmental conditions and their overlap had on the variation in assemblage composition. Our models explained a high percentage of variation in assemblage composition (59-65%) and showed that spatial structure consistent with marine compartmentalization played a more important role than local environmental conditions. At least during the study period, surface currents connecting sites within the two compartments failed to generate sufficient dispersal to offset the impact of differences due to compartmentalization. In other words, our findings suggest that, even for a prototypical cosmopolitan group, everything is not everywhere.

Mobile Phones As Surveillance Tools: Implementing and Evaluating a Large-Scale Intersectoral Surveillance System for Rabies in Tanzania.

Katie Hampson and colleagues describe their experience of developing and deploying a large-scale rabies surveillance system based on mobile phones in southern Tanzania.

An extended period of elevated influenza mortality risk follows the main waves of influenza pandemics.

Understanding the extent and evolution of pandemic-induced mortality risk is critical given its wide-ranging impacts on population health and socioeconomic outcomes. We examine empirically the persistence and scale of influenza mortality risk following the main waves of influenza pandemics, a quantitative analysis of which is required to understand the true scale of pandemic-induced risk. We provide evidence from municipal public health records that multiple recurrent outbreaks followed the main waves of the 1918-19 pandemic in eight large cities in the UK, a pattern we confirm using data for the same period in the US and data for multiple influenza pandemics during the period 1838-2000 in England and Wales. To estimate the persistence and scale of latent post-pandemic influenza mortality risk, we model the stochastic process of mortality rates as a sequence of bounded Pareto distributions whose tail indexes evolves over time. Consistently across pandemics and locations, we find that influenza mortality risk remains elevated for around two decades after the main pandemic waves before more rapid convergence to background influenza mortality, amplifying the impact of pandemics. Despite the commonality in duration, there is heterogeneity in the persistence and scale of risk across the cities, suggesting effects of both immunity and socioeconomic conditions.

Trends in the diversity of mortality causes and age-standardised mortality rates among subpopulations within Scotland, 2001-2019.

Previous research has demonstrated increasing diversity in causes of mortality among high-income nations in recent decades, associated with improvements in health and increasing life expectancies. Health outcomes are known to vary widely between communities within these countries and inequalities between sexes and other subpopulations are key in understanding the health of populations. Despite this, little is known about variation in the diversity of mortality causes between these subpopulations. Diversification in mortality causes indicates an increase in the pool of potential causes of mortality an individual is likely to face. This poses challenges for the public health and medical sectors by increasing diagnostic uncertainty and broadening the range of causes to be addressed by public health and medical interventions. Here we examine trends over time in the diversity in causes of mortality in Scotland by sex and area-level deprivation, also examining deaths among those younger than 75 years and those 75 years and older separately. We find that diversity in causes of mortality has increased across subpopulations; that it has risen more quickly in men than women; that the rate of increase has been similar across age categories; and that there is no clear ranking in the trends by deprivation quintile, despite slower improvements in mortality rates among the most deprived. Increasing diversity in mortality causes suggests that a greater public health focus on reducing death rates from a broader range of causes is likely to be required, and this may be especially important for men who face a faster rate of diversification.

Widespread extinction debts and colonization credits in United States breeding bird communities.

Species extinctions and colonizations in response to land cover change often occur with time lags rather than instantaneously, leading to extinction debts and colonization credits. These debts and credits can lead to erroneous predictions of future biodiversity. Recent attempts to measure debts and credits have been limited to small geographical areas and have not considered multiple land cover types, or the directionality of land cover change. Here we quantify the relative contribution of past and current landscapes on the current effective number of species of 2,880 US bird communities, explicitly measuring the response of biodiversity to increases and decreases in five land cover types. We find that the current effective number of species is still largely explained by the past landscape composition (legacy effect), depending on the type, magnitude and directionality of recent land cover change. This legacy effect leads to widespread extinction debts and colonization credits. Specifically, we reveal debts across 52% of the United States, particularly in recently urbanized areas, and colonization credits in the remaining 48%, which are primarily associated with grassland decrease. We conclude that biodiversity policy targets risk becoming rapidly obsolete unless past landscapes are considered and debts and credits accounted for.

Rabies shows how scale of transmission can enable acute infections to persist at low prevalence.

How acute pathogens persist and what curtails their epidemic growth in the absence of acquired immunity remains unknown. Canine rabies is a fatal zoonosis that circulates endemically at low prevalence among domestic dogs in low- and middle-income countries. We traced rabies transmission in a population of 50,000 dogs in Tanzania from 2002 to 2016 and applied individual-based models to these spatially resolved data to investigate the mechanisms modulating transmission and the scale over which they operate. Although rabies prevalence never exceeded 0.15%, the best-fitting models demonstrated appreciable depletion of susceptible animals that occurred at local scales because of clusters of deaths and dogs already incubating infection. Individual variation in rabid dog behavior facilitated virus dispersal and cocirculation of virus lineages, enabling metapopulation persistence. These mechanisms have important implications for prediction and control of pathogens that circulate in spatially structured populations.

An Integrated Framework for Process-Driven Model Construction in Disease Ecology and Animal Health.

Process models that focus on explicitly representing biological mechanisms are increasingly important in disease ecology and animal health research. However, the large number of process modelling approaches makes it difficult to decide which is most appropriate for a given disease system and research question. Here, we discuss different motivations for using process models and present an integrated conceptual analysis that can be used to guide the construction of infectious disease process models and comparisons between them. Our presentation complements existing work by clarifying the major differences between modelling approaches and their relationship with the biological characteristics of the epidemiological system. We first discuss distinct motivations for using process models in epidemiological research, identifying the key steps in model design and use associated with each. We then present a conceptual framework for guiding model construction and comparison, organised according to key aspects of epidemiological systems. Specifically, we discuss the number and type of disease states, whether to focus on individual hosts (e.g., cows) or groups of hosts (e.g., herds or farms), how space or host connectivity affect disease transmission, whether demographic and epidemiological processes are periodic or can occur at any time, and the extent to which stochasticity is important. We use foot-and-mouth disease and bovine tuberculosis in cattle to illustrate our discussion and support explanations of cases in which different models are used to address similar problems. The framework should help those constructing models to structure their approach to modelling decisions and facilitate comparisons between models in the literature.

Toward Elimination of Dog-Mediated Human Rabies: Experiences from Implementing a Large-scale Demonstration Project in Southern Tanzania.

A Rabies Elimination Demonstration Project was implemented in Tanzania from 2010 through to 2015, bringing together government ministries from the health and veterinary sectors, the World Health Organization, and national and international research institutions. Detailed data on mass dog vaccination campaigns, bite exposures, use of post-exposure prophylaxis (PEP), and human rabies deaths were collected throughout the project duration and project areas. Despite no previous experience in dog vaccination within the project areas, district veterinary officers were able to implement district-wide vaccination campaigns that, for most part, progressively increased the numbers of dogs vaccinated with each phase of the project. Bite exposures declined, particularly in the southernmost districts with the smallest dog populations, and health workers successfully transitioned from primarily intramuscular administration of PEP to intradermal administration, resulting in major cost savings. However, even with improved PEP provision, vaccine shortages still occurred in some districts. In laboratory diagnosis, there were several logistical challenges in sample handling and submission but compared to the situation before the project started, there was a moderate increase in the number of laboratory samples submitted and tested for rabies in the project areas with a decrease in the proportion of rabies-positive samples over time. The project had a major impact on public health policy and practice with the formation of a One Health Coordination Unit at the Prime Minister's Office and development of the Tanzania National Rabies Control Strategy, which lays a roadmap for elimination of rabies in Tanzania by 2030 by following the Stepwise Approach towards Rabies Elimination (SARE). Overall, the project generated many important lessons relevant to rabies prevention and control in particular and disease surveillance in general. Lessons include the need for (1) a specific unit in the government for managing disease surveillance; (2) application of innovative data collection and management approaches such as the use of mobile phones; (3) close cooperation and effective communication among all key sectors and stakeholders; and (4) flexible and adaptive programs that can incorporate new information to improve their delivery, and overcome challenges of logistics and procurement.

Assembling evidence for identifying reservoirs of infection.

Many pathogens persist in multihost systems, making the identification of infection reservoirs crucial for devising effective interventions. Here, we present a conceptual framework for classifying patterns of incidence and prevalence, and review recent scientific advances that allow us to study and manage reservoirs simultaneously. We argue that interventions can have a crucial role in enriching our mechanistic understanding of how reservoirs function and should be embedded as quasi-experimental studies in adaptive management frameworks. Single approaches to the study of reservoirs are unlikely to generate conclusive insights whereas the formal integration of data and methodologies, involving interventions, pathogen genetics, and contemporary surveillance techniques, promises to open up new opportunities to advance understanding of complex multihost systems.