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Mathematical models are increasingly adopted for setting disease prevention and control targets. As model-informed policies are implemented, however, the inaccuracies of some forecasts become apparent, for example overprediction of infection burdens and intervention impacts. Here, we attribute these discrepancies to methodological limitations in capturing the heterogeneities of real-world systems. The mechanisms underpinning risk factors of infection and their interactions determine individual propensities to acquire disease. These factors are potentially so numerous and complex that to attain a full mechanistic description is likely unfeasible. To contribute constructively to the development of health policies, model developers either leave factors out (reductionism) or adopt a broader but coarse description (holism). In our view, predictive capacity requires holistic descriptions of heterogeneity which are currently underutilised in infectious disease epidemiology, in comparison to other population disciplines, such as non-communicable disease epidemiology, demography, ecology and evolution. [ABSTRACT FROM AUTHOR]

The overall malaria burden in the Americas has decreased dramatically over the past two decades, but residual transmission pockets persist across the Amazon Basin, where Plasmodium vivax is the predominant infecting species. Current elimination efforts require a better quantitative understanding of malaria transmission dynamics for planning, monitoring, and evaluating interventions at the community level. This can be achieved with mathematical models that properly account for risk heterogeneity in communities approaching elimination, where few individuals disproportionately contribute to overall malaria prevalence, morbidity, and onwards transmission. Here we analyse demographic information combined with routinely collected malaria morbidity data from the town of Mâncio Lima, the main urban transmission hotspot of Brazil. We estimate the proportion of high-risk subjects in the host population by fitting compartmental susceptible-infected-susceptible (SIS) transmission models simultaneously to age-stratified vivax malaria incidence densities and the frequency distribution of P. vivax malaria attacks experienced by each individual over 12 months. Simulations with the best-fitting SIS model indicate that 20% of the hosts contribute 86% of the overall vivax malaria burden. Despite the low overall force of infection typically found in the Amazon, about one order of magnitude lower than that in rural Africa, high-risk individuals gradually develop clinical immunity following repeated infections and eventually constitute a substantial infectious reservoir comprised of asymptomatic parasite carriers that is overlooked by routine surveillance but likely fuels onwards malaria transmission. High-risk individuals therefore represent a priority target for more intensive and effective interventions that may not be readily delivered to the entire community. Author summary: Malaria transmission models that disregard risk heterogeneity at the community level, classifying individuals as uniformly susceptible or infected, may not properly recapitulate the epidemiology of malaria in real-life settings. Here we fit a compartmental susceptible-infected-susceptible model to malaria morbidity data from Mâncio Lima, the main urban transmission hotspot of Brazil, and estimate that 20% of the urban residents contribute 86% of the overall vivax malaria burden in the town. Despite the low average force of infection, one order of magnitude lower that in rural Africa, high-risk individuals experience enough repeated infections to develop clinical immunity and constitute an asymptomatic reservoir that fuels onwards malaria transmission. Therefore, these high-risk subjects account for the paradoxical finding of clinical immunity and frequent asymptomatic parasite carriage in low-endemicity Amazonian communities. We argue that mathematical models accounting for risk heterogeneity are crucial to plan and evaluate malaria control and elimination interventions targeted to high-risk groups in communities, municipalities, and regions. [ABSTRACT FROM AUTHOR]

The article presents a study which described the key drivers of heterogeneity in tuberculosis (TB) burden and the challenges in quantifying this heterogeneity. Topics discussed include factors that contribute to heterogeneity, examples of specific forms of heterogeneity and ways forward, and challenges in quantifying heterogeneity.

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Setting global strategies and targets for disease prevention and control often involves mathematical models. Model structure is typically subject to intense scrutiny, such as confrontation with empirical data and alternative formulations, while a less frequently challenged aspect is the widely adopted reduction of parameters to their average values. Focusing on endemic diseases, we use a general transmission model to explain how mean field approximations decrease the estimated R 0 from prevalence data, while threshold phenomena – such as the epidemic and reinfection thresholds – remain invariant. This results in an underestimation of the effort required to control disease, which may be particularly severe when the approximation inappropriately places transmission estimates below important thresholds. These concepts are widely applicable across endemic pathogen systems. [ABSTRACT FROM AUTHOR]

Where malaria is transmitted by zoophilic vectors, two types of malaria control strategies have been proposed based on animals: using livestock to divert vector biting from people (zooprophylaxis) or as baits to attract vectors to insecticide sources (insecticide-treated livestock). Opposing findings have been obtained on malaria zooprophylaxis, and despite the success of an insecticide-treated livestock trial in Pakistan, where malaria vectors are highly zoophilic, its effectiveness is yet to be formally tested in Africa where vectors are more anthropophilic. This study aims to clarify the different effects of livestock on malaria and to understand under what circumstances livestock-based interventions could play a role in malaria control programmes. This was explored by developing a mathematical model and combining it with data from Pakistan and Ethiopia. Consistent with previous work, a zooprophylactic effect of untreated livestock is predicted in two situations: if vector population density does not increase with livestock introduction, or if livestock numbers and availability to vectors are sufficiently high such that the increase in vector density is counteracted by the diversion of bites from humans to animals. Although, as expected, insecticide-treatment of livestock is predicted to be more beneficial in settings with highly zoophilic vectors, like South Asia, we find that the intervention could also considerably decrease malaria transmission in regions with more anthropophilic vectors, like Anopheles arabiensis in Africa, under specific circumstances: high treatment coverage of the livestock population, using a product with stronger or longer lasting insecticidal effect than in the Pakistan trial, and with small (ideally null) repellency effect, or if increasing the attractiveness of treated livestock to malaria vectors. The results suggest these are the most appropriate conditions for field testing insecticide-treated livestock in an Africa region with moderately zoophilic vectors, where this intervention could contribute to the integrated control of malaria and livestock diseases. [ABSTRACT FROM AUTHOR]

After remarkable success of vector control campaigns worldwide, concerns about loss of immunity against Plasmodium falciparum due to lack of exposure to the parasite are relevant since an increase of severe cases in less immune individuals is expected. We present a mathematical model to investigate the impact of reducing exposure to the parasite on the immune repertoire against P. falciparum erythrocyte membrane protein 1 (PfEMP1) variants. The model was parameterized with data from Príncipe Island, West Africa, and applied to simulate two alternative transmission scenarios: one where control measures are continued to eventually drive the system to elimination; and another where the effort is interrupted after 6 years of its initiation and the system returns to the initial transmission potential. Population dynamics of parasite prevalence predict that in a few years infection levels return to the pre-control values, while the re-acquisition of the immune repertoire against PfEMP1 is slower, creating a window for increased severity. The model illustrates the consequences of loss of immune repertoire against PfEMP1 in a given setting and can be applied to other regions where similar data may be available. [ABSTRACT FROM AUTHOR]

We first study an SIR system of differential equations with periodic coefficients describing an epidemic in a seasonal environment. Unlike in a constant environment, the final epidemic size may not be an increasing function of the basic reproduction number R0 or of the initial fraction of infected people. Moreover, large epidemics can happen even if R0 < 1. But like in a constant environment, the final epidemic size tends to 0 when R0 < 1 and the initial fraction of infected people tends to 0. When R0 > 1, the final epidemic size is bigger than the fraction 1-1/R0 of the initially nonimmune population. In summary, the basic reproduction number R0 keeps its classical threshold property but many other properties are no longer true in a seasonal environment. These theoretical results should be kept in mind when analyzing data for emerging vector-borne diseases (West-Nile, dengue, chikungunya) or air-borne diseases (SARS, pandemic influenza); all these diseases being influenced by seasonality. [ABSTRACT FROM AUTHOR]

We introduce a model for assessing the levels and patterns of genetic diversity in pathogen populations, whose epidemiology follows a susceptible-infected-recovered model (SIR). We model the population of pathogens as a metapopulation composed of subpopulations (infected hosts), where pathogens replicate and mutate. Hosts transmit pathogens to uninfected hosts. We show that the level of pathogen variation is well predicted by analytical expressions, such that pathogen neutral molecular variation is bounded by the level of infection and increases with the duration of infection. We then introduce selection in the model and study the invasion probability of a new pathogenic strain whose fitness (R0(1+s)) is higher than the fitness of the resident strain (R0). We show that this invasion probability is given by the relative increment in R0 of the new pathogen (s). By analyzing the patterns of genetic diversity in this framework, we identify the molecular signatures during the replacement and compare these with those observed in sequences of influenza A. [ABSTRACT FROM AUTHOR]

Introduction: Alagoas is one of the poorest states of Brazil and its HDI is the country's worst. Objectives: Present the epidemiological profile of suicides that occurred in the State of Alagoas from 2008 to 2018. Methods: This research is epidemiological, descriptive and transversal. In this sense, data from the Universal Health System Informatics Department (DATASUS) were used to analyze the age range, marital status, race, sex, education and cause of death of the suicide victims. Results: 1245 people committed suicide in Alagoas in the period of 10 years, they were 951 men (76%) and 294 women (24%). The main cause of death was self-harm caused by hanging, strangulation and suffocation (ICD X-70), occurring in approximately 67% of cases (836 people), followed by self-poisoning by drugs and medication (ICD X-64) 140 people, and pesticides (CID X-68) 92 people. The auto injuries caused by firearms (ICD X-72 to X-74) totalled 45 victims, while the self-inflicted injuries intentionally caused by precipitation from a high place (ICD X-80) totalled 38 victims. Most of those who took their lives were single (57%), brown (88%), had between 15 and 39 years old (55%) and did not have their education level informed (75%). Conclusions: Thus, the present study demonstrated that there is a compromise of important statistical data on education level and there is the inexistence of data on family income and sexual orientation, which may help to understand the phenomenon of suicide in Alagoas. Despite all this, it was possible to identify a group of risk for suicide in the State: brown, single and young men. [ABSTRACT FROM AUTHOR]

The SIR (susceptible–infectious–resistant) and SIS (susceptible–infectious–susceptible) frameworks for infectious disease have been extensively studied and successfully applied. They implicitly assume the upper and lower limits of the range of possibilities for host immune response. However, the majority of infections do not fall into either of these extreme categories. We combine two general avenues that straddle this range: temporary immune protection (immunity wanes over time since infection), and partial immune protection (immunity is not fully protective but reduces the risk of reinfection). We present a systematic analysis of the dynamics and equilibrium properties of these models in comparison to SIR and SIS, and analyse the outcome of vaccination programmes. We describe how the waning of immunity shortens inter-epidemic periods, and poses major difficulties to disease eradication. We identify a “reinfection threshold” in transmission when partial immunity is included. Below the reinfection threshold primary infection dominates, levels of infection are low, and vaccination is highly effective (approximately an SIR model). Above the reinfection threshold reinfection dominates, levels of infection are high, and vaccination fails to protect (approximately an SIS situation). This association between high prevalence of infection and vaccine failure emphasizes the problems of controlling recurrent infections in high-burden regions. However, vaccines that induce a better protection than natural infection have the potential to increase the reinfection threshold, and therefore constitute interventions with a surprisingly high capacity to reduce infection where reduction is most needed. [Copyright &y& Elsevier]

Version of Record

Abstract: Heterogeneity in susceptibility and infectivity is inherent to infectious disease transmission in nature. Here we are concerned with the formulation of mathematical models that capture the essence of heterogeneity while keeping a simple structure suitable of analytical treatment. We explore the consequences of host heterogeneity in the susceptibility to infection for epidemiological models for which immunity conferred by infection is partially protective, known as susceptible-infected-recovered-infected (SIRI) models. We analyze the impact of heterogeneity on disease prevalence and contrast the susceptibility profiles of the subpopulations at risk for primary infection and reinfection. We present a systematic study in the case of two frailty groups. We predict that the average rate of reinfection may be higher than the average rate of primary infection, which may seem paradoxical given that primary infection induces life-long partial protection. Infection generates a selection mechanism whereby fit individuals remain in and frail individuals are transferred to . If this effect is strong enough we have a scenario where, on average, the rate of reinfection is higher than the rate of primary infection even though each individual has a risk reduction following primary infection. This mechanism may explain high rates of tuberculosis reinfection recently reported. Finally, the enhanced benefits of vaccination strategies that target the high-risk groups are quantified. [Copyright &y& Elsevier]