Onchocerciasis-associated epilepsy in Maridi, South Sudan: Modelling and exploring the impact of control measures against river blindness.

BACKGROUND: Onchocerciasis, also known as "river blindness", is caused by the bite of infected female blackflies (genus Simuliidae) that transmit the parasite Onchocerca volvulus. A high onchocerciasis microfarial load increases the risk to develop epilepsy in children between the ages of 3 and 18 years. In resource-limited settings in Africa where onchocerciasis has been poorly controlled, high numbers of onchocerciasis-associated epilepsy (OAE) are reported. We use mathematical modeling to predict the impact of onchocerciasis control strategies on the incidence and prevalence of OAE. METHODOLOGY: We developed an OAE model within the well-established mathematical modelling framework ONCHOSIM. Using Latin-Hypercube Sampling (LHS), and grid search technique, we quantified transmission and disease parameters using OAE data from Maridi County, an onchocerciasis endemic area, in southern Republic of South Sudan. Using ONCHOSIM, we predicted the impact of ivermectin mass drug administration (MDA) and vector control on the epidemiology of OAE in Maridi. PRINCIPAL FINDINGS: The model estimated an OAE prevalence of 4.1% in Maridi County, close to the 3.7% OAE prevalence reported in field studies. The OAE incidence is expected to rapidly decrease by >50% within the first five years of implementing annual MDA with good coverage (≥70%). With vector control at a high efficacy level (around 80% reduction of blackfly biting rates) as the sole strategy, the reduction is slower, requiring about 10 years to halve the OAE incidence. Increasing the efficacy levels of vector control, and implementing vector control simultaneously with MDA, yielded better results in preventing new cases of OAE. CONCLUSIONS/SIGNIFICANCES: Our modeling study demonstrates that intensifying onchocerciasis eradication efforts could substantially reduce OAE incidence and prevalence in endemic foci. Our model may be useful for optimizing OAE control strategies.

An evolutionary game model of individual choices and bed net use: elucidating key aspect in malaria elimination strategies.

Insecticide-treated net (ITN) is the most applicable and cost-effective malaria intervention measure in sub-Saharan Africa and elsewhere. Although ITNs have been widely distributed to malaria-endemic regions in the past, their success has been threatened by misuses (in fishing, agriculture etc.) and decay in ITN efficacy. Decision-making in using the ITNs depends on multiple coevolving factors: malaria prevalence, mosquito density, ITN availability and its efficacy, and other socio-economic determinants. While ITN misuse increases as the efficacy of ITNs declines, high efficacy also impedes proper use due to free-riding. This irrational usage leads to increased malaria prevalence, thereby worsening malaria control efforts. It also remains unclear if the optimum ITN use for malaria elimination can be achieved under such an adaptive social learning process. Here, we incorporate evolutionary game theory into a disease transmission model to demonstrate these behavioural interactions and their impact on malaria prevalence. We show that social optimum usage is a function of transmission potential, ITN efficacy and mosquito demography. Under specific parameter regimes, our model exhibits patterns of ITN usage similar to observed data from parts of Africa. Our study suggests that the provision of financial incentives as prompt feedback to improper ITN use can reduce misuse and contribute positively towards malaria elimination efforts in Africa and elsewhere.

Disparity in socio-economic status explains the pattern of self-medication of antibiotics in India: understanding from game-theoretic perspective.

The emergence of antimicrobial resistance has raised great concern for public health in many lower-income countries including India. Socio-economic determinants like poverty, health expenditure and awareness accelerate this emergence by influencing individuals' attitudes and healthcare practices such as self-medication. This self-medication practice is highly prevalent in many countries, where antibiotics are available without prescriptions. Thus, complex dynamics of drug- resistance driven by economy, human behaviour, and disease epidemiology poses a serious threat to the community, which has been less emphasized in prior studies. Here, we formulate a game-theoretic model of human choices in self-medication integrating economic growth and disease transmission processes. We show that this adaptive behaviour emerges spontaneously in the population through a self-reinforcing process and continual feedback from the economy, resulting in the emergence of resistance as externalities of human choice under resource constraints situations. We identify that the disparity between social-optimum and individual interest in self-medication is primarily driven by the effectiveness of treatment, health awareness and public health interventions. Frequent multiple-peaks of resistant strains are also observed when individuals imitate others more readily and self-medication is more likely. Our model exemplifies that timely public health intervention for financial risk protection, and antibiotic stewardship policies can improve the epidemiological situation and prevent economic collapse.

The effect of human vaccination behaviour on strain competition in an infectious disease: An imitation dynamic approach.

Strain competition plays an important role in shaping the dynamics of multiple pathogen outbreaks in a population. Competition may lead to exclusion of some pathogens, while it may influence the invasion of an emerging mutant in the population. However, little emphasis has been given to understand the influence of human vaccination choice on pathogen competition or strain invasion for vaccine-preventable infectious diseases. Coupling game dynamic framework of vaccination choice and compartmental disease transmission model of two strains, we explore invasion and persistence of a mutant in the population despite having a lower reproduction rate than the resident one. We illustrate that higher perceived strain severity and lower perceived vaccine efficacy are necessary conditions for the persistence of a mutant strain. The numerical simulation also extends these invasion and persistence analyses under asymmetric cross-protective immunity of these strains. We show that the dynamics of this cross-immunity model under human vaccination choices is determined by the interplay of parameters defining the cross-immune response function, perceived risk of infection, and vaccine efficacy, and it can exhibit invasion and persistence of mutant strain, even complete exclusion of resident strain in the regime of sufficiently high perceived risk. We conclude by discussing public health implications of the results, that proper risk communication in public about the severity of the disease is an important task to reduce the chance of mutant invasion. Thus, understanding pathogen competitions under social interactions and choices may be an important component for policymakers for strategic decision-making.

Optimal governance and implementation of vaccination programmes to contain the COVID-19 pandemic.

Since the recent introduction of several viable vaccines for SARS-CoV-2, vaccination uptake has become the key factor that will determine our success in containing the COVID-19 pandemic. We argue that game theory and social network models should be used to guide decisions pertaining to vaccination programmes for the best possible results. In the months following the introduction of vaccines, their availability and the human resources needed to run the vaccination programmes have been scarce in many countries. Vaccine hesitancy is also being encountered from some sections of the general public. We emphasize that decision-making under uncertainty and imperfect information, and with only conditionally optimal outcomes, is a unique forte of established game-theoretic modelling. Therefore, we can use this approach to obtain the best framework for modelling and simulating vaccination prioritization and uptake that will be readily available to inform important policy decisions for the optimal control of the COVID-19 pandemic.

Human choice to self-isolate in the face of the COVID-19 pandemic: A game dynamic modelling approach.

Non-pharmaceutical interventions (NPIs) involving social-isolation strategies such as self-quarantine (SQ) and social-distancing (SD) are useful in controlling the spread of infections that are transmitted through human-to-human contacts, e.g., respiratory diseases such as COVID-19. In the absence of a safe and effective cure or vaccine during the first ten months of the COVID-19 pandemic, countries around the world implemented these social-isolation strategies and other NPIs to reduce COVID-19 transmission. But, individual and public perception play a crucial role in the success of any social-isolation measure. Thus, in spite of governments' initiatives to use NPIs to combat COVID-19 in many countries around the world, individual choices rendered social-isolation unsuccessful in some of these countries. This resulted in huge outbreaks that imposed a substantial morbidity, mortality, hospitalization, economic, etc., toll on human lives. In particular, human choices pose serious challenges to public health strategic decision-making in controlling the COVID-19 pandemic. To unravel the impact of this behavioral response to social-isolation on the burden of the COVID-19 pandemic, we develop a model framework that integrates COVID-19 transmission dynamics with a multi-strategy evolutionary game approach of individual decision-making. We use this integrated framework to characterize the evolution of human choices in social-isolation as the disease progresses and public health control measures such as mandatory lockdowns are implemented. Analysis of the model illustrates that SD plays a major role in reducing the burden of the disease compared to SQ. Parameter estimation using COVID-19 incidence data, as well as different lockdown data sets from India, and scenario analysis involving a combination of Voluntary-Mandatory implementation of SQ and SD shows that the effectiveness of this approach depends on the type of isolation, and the time and period of implementation of the selected isolation measure during the outbreak.

The epidemiology of tuberculosis-associated hyperglycemia in individuals newly screened for type 2 diabetes mellitus: systematic review and meta-analysis.

BACKGROUND: There is scarce evidence that tuberculosis (TB) can cause diabetes in those not previously known to be diabetic. Whilst the World Health Organization (WHO) recommends screening for Diabetes Mellitus (DM) at the onset of TB treatment, nevertheless, it remains to be elucidated which patients with TB-associated hyperglycemia are at higher risk for developing DM and stand to benefit from a more regular follow-up. This review aims to firstly quantify the reduction of newly detected hyperglycemia burden in TB patients who are on treatment over time; secondly, determine the burden of TB-associated hyperglycemia after follow-up, and thirdly, synthesize literature on risk factors for unresolved TB-associated hyperglycemia in previously undiagnosed individuals. METHODS: We searched PUBMED, EMBASE, SCOPUS, and Global Health for articles on TB-associated hyperglycemia up to September 30th, 2019. Search terms included Tuberculosis and hyperglycemia/DM, and insulin resistance. We appraised studies, extracted data, and conducted a meta-analysis to assess the change of the burden of hyperglycemia in prospective studies. The review is registered in the PROSPERO database (CRD42019118173). RESULTS: Eleven studies were included in the meta-analysis yielding a total of 677 (27,3%) of patients with newly detected hyperglycemia at baseline. The mean quality score of eligible studies using the Newcastle-Ottawa Quality Assessment Scale was 7.1 out of 9 (range 6-9). The pooled unresolved new cases of hyperglycemia at the end of follow up was 50% (95% CI: 36-64%) and the total pooled burden of hyperglycemia at 3-6 months of follow up was 11% (95% CI: 7-16%), with both estimates displaying a high heterogeneity, which remained significant after performing a sub-analysis by DM diagnostic method and 3 months of follow up. As only 2 studies explored risk factors for unresolved hyperglycemia, no meta-analysis was performed on risk factors. CONCLUSION: Our meta-analysis showed that although in half of the patients with newly observed hyperglycemia at baseline, it remained unresolved at a follow-up of 3 to 6 months, the total burden of hyperglycemia is slightly above 10%, 3 months after initiating TB treatment. Studies are warranted to assess whether risk factors including HIV positivity, smoking, and extensive pulmonary TB disease put patients at higher risk for DM.

Optimal Management of Public Perceptions During A Flu Outbreak: A Game-Theoretic Perspective.

Public perceptions and sentiments play a crucial role in the success of vaccine uptake in the community. While vaccines have proven to be the best preventive method to combat the flu, the attitude and knowledge about vaccines are a major hindrance to higher uptake in most of the countries. The yearly coverage, especially in the vulnerable groups in the population, often remains below the herd immunity level despite the Flu Awareness Campaign organized by WHO every year worldwide. This brings immense challenges to the nation's public health protection agency for strategic decision-making in controlling the flu outbreak every year. To understand the impact of public perceptions and vaccination decisions while designing optimal immunization policy, we model the individual decision-making as a two-strategy pairwise contest game, where pay-off is considered as a function of public health effort for the campaign. We use Pontryagin's maximum principle to identify the best possible strategy for public health to implement vaccination and reduce infection at a minimum cost. Our optimal analysis shows that the cost of public health initiatives is qualitatively and quantitatively different under different public perceptions and attitudes towards vaccinations. When individual risk perception evolves with vaccine uptake or disease induced death, our model demonstrates a feed-forward mechanism in the dynamics of vaccination and exhibits an increase in vaccine uptake. Using numerical simulation, we also observe that the optimal cost can be minimized by putting the effort in the beginning and later part of the outbreak rather than during the peak. It confers that public health efforts towards disseminating disease severity or actual vaccination risk might accelerate the vaccination coverage and mitigate the infection faster.

Author Correction: Antibiotic drug-resistance as a complex system driven by socio-economic growth and antibiotic misuse.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

The epidemiology of intransient TB-induced hyperglycaemia in previously undiagnosed diabetes mellitus 2 individuals: a protocol for a systematic review and meta-analysis.

BACKGROUND: Diabetes mellitus (DM) is burgeoning as a global chronic health condition. Some studies suggest that tuberculosis (TB) can even cause diabetes in those not previously known to be diabetic, which as a corollary can add to the already heavy global DM burden. The World Health Organization (WHO) recommends screening for DM at the start of TB treatment; however, it remains to be elucidated which patients with TB-induced hyperglycaemia are at risk for developing DM and who would benefit from a more regular follow-up. This systematic review will aim to firstly synthesise literature on the irreversibility of TB-induced hyperglycaemia in individuals with previously undiagnosed type 2 diabetes mellitus and secondly to synthesise literature on risk factors for progression from TB-induced hyperglycaemia to overt DM in previously undiagnosed. METHODS: We will search for relevant studies in electronic databases such as PubMed, EMBASE, PROQUEST, and SCOPUS. Furthermore, references will be hand searched to identify other studies. A flow diagram will be drawn to identify the studies retrieved from each database. We will review all publications that include studies containing data on impaired glucose metabolism upon TB diagnosis, and the quality of all eligible studies will be assessed using the Newcastle-Ottawa Scale. We will further conduct a meta-analysis to pool estimates on the risk of progression of persistent hyperglycaemia to overt DM within this population group, as well as the risk factors for this progression. We will use a random effect model to assess heterogeneity, will carry out sensitivity analysis to explore the influence of a single study on the overall estimate, and will report our findings from our systematic review and meta-analysis according to PRISMA guidelines. Egger's test will be performed to explore the presence of selective reporting bias. If data allow, we will perform a subgroup/meta-regression analysis. Summary effects will be reported using odds ratio, hazard ratio, and relative risk ratios. Furthermore, any clinical, epidemiological, and public health research gaps we identify will be described in a research proposal.

Antibiotic drug-resistance as a complex system driven by socio-economic growth and antibiotic misuse.

Overwhelming antibiotic use poses a serious challenge today to the public-health policymakers worldwide. Many empirical studies pointed out this ever-increasing antibiotic consumption as primary driver of the community-acquired antibiotic drug-resistance, especially in the middle- and lower-income countries. The association is well documented across spatio-temporal gradients in many parts of the world, but there is rarely any study that emphasizes the mechanism of the association, which is important for combating drug-resistance. Formulating a mathematical model of emergence and transmission of drug-resistance, we in this paper, present how amalgamating three components: socio-economic growth, population ecology of infectious disease, and antibiotic misuse can instinctively incite proliferation of resistance in the society. We show that combined impact of economy, infections, and self-medication yield synergistic interactions through feedbacks on each other, presenting the emergence of drug-resistance as a self-reinforcing cycle in the population. Analysis of our model not only determines the threshold of antibiotic use beyond which the emergence of resistance may occur, but also characterizes how fast it develops depending on economic growth, and lack of education and awareness of the population. Our model illustrates that proper and timely government aid in population health can break the self-reinforcing process and reduce the burden of drug-resistance in the community.

The impact of rare but severe vaccine adverse events on behaviour-disease dynamics: a network model.

The propagation of rumours about rare but severe adverse vaccination or infection events through social networks can strongly impact vaccination uptake. Here we model a coupled behaviour-disease system where individual risk perception regarding vaccines and infection are shaped by their personal experiences and the experiences of others. Information about vaccines and infection either propagates through the network or becomes available through globally available sources. Dynamics are studied on a range of network types. Individuals choose to vaccinate according to their personal perception of risk and information about infection prevalence. We study events ranging from common and mild, to severe and rare. We find that vaccine and infection adverse events have asymmetric impacts. Vaccine (but not infection) adverse events may significantly prolong the tail of an outbreak. Similarly, introducing a small risk of a vaccine adverse event may cause a steep decline in vaccine coverage, especially on scale-free networks. Global dissemination of information about infection prevalence boosts vaccine coverage more than local dissemination. Taken together, these findings highlight the dangers associated with vaccine rumour propagation through scale-free networks such as those exhibited by online social media, as well as the benefits of disseminating public health information through mass media.

Game dynamic model of optimal budget allocation under individual vaccination choice.

Communicable diseases are leading cause of child mortality in developing and under-developed countries. Public health ministries in states and country allocate a considerable amount of budget every year for vaccination campaigns to control infections. Even third-party agencies such as Gates Foundation, UNDP, GAVI, World Bank, WHO also allocate huge funds to under-developed and developing countries for vaccination programs and disease eliminations. However, economic constraints and current disease prevalence are not enough driving factors for optimal decisions in budget allocations for vaccinations and controlling the disease. In a population under voluntary vaccination campaign, high vaccine coverage cannot be taken for granted, as individuals' free-riding behaviour plays a significant role in achieving the herd immunity level coverage. Individual-level vaccine exemptions and ignoring this important component by the policymakers are key determinants for failure of disease elimination program these days in many under-developed and developing countries. We integrate evolutionary game theory and compartmental model of disease transmission to analyze how individual vaccination choice influence the budget allocations and vice-versa. Our model illustrates that individuals' perceived risk plays an important role in optimal budget allocations to minimize infections. Analyses of our model indicate that the optimal distribution of third-party funds may be very different than usual, especially in multiple populations with contrasting demographic and economic profiles. These findings are certainly useful to public health policymakers and may help to quantify certain parameters in budget allocations to control vaccine-preventable diseases.

High prevalence of onchocerciasis-associated epilepsy in villages in Maridi County, Republic of South Sudan: A community-based survey.

PURPOSE: To determine the prevalence and incidence of epilepsy in an onchocerciasis endemic region of South Sudan. METHODS: In May 2018, a door-to-door household survey was conducted in 8 study sites in an onchocerciasis endemic area in Maridi County. RESULTS: A total of 2511 households agreed to participate in the study, corresponding to 17,652 individuals. An epilepsy screening questionnaire identified 799 persons suspected to have epilepsy (4.5%); in 736 of the 766 persons (96.1%) seen by a clinical officer the diagnosis of epilepsy was confirmed. Adding 38 persons who were not seen but with a positive answer to a combination of screening questions, 774 persons (4.4%) had epilepsy. Epilepsy prevalence was highest in the 11-20 age group (10.5%); 66 persons with epilepsy (PWE) developed their first seizures in the year preceding the survey (annual incidence = 373.9/100.000). Neurocysticercosis cannot explain the high epilepsy prevalence since no pigs are kept in the area. Independent risk factors for epilepsy included male gender, belonging to a "permanent household" and a farming family, and living in a village bordering the Maridi River. Only 7209 (40.8%) of the population took ivermectin in 2017. CONCLUSION: A very high prevalence and incidence of epilepsy was observed in several villages in Maridi County located close to the Maridi River and the Maridi dam. Urgent action is needed to prevent children in Maridi County from developing OAE by strengthening the onchocerciasis elimination program.

Clinical characteristics of onchocerciasis-associated epilepsy in villages in Maridi County, Republic of South Sudan.

PURPOSE: To describe the clinical manifestations of persons with epilepsy (PWE) in onchocerciasis endemic villages in South Sudan. METHODS: During a survey in Maridi County in May 2018, PWE were interviewed and examined in their households by a clinical officer or medical doctor. Onchocerciasis-associated epilepsy (OAE) was defined as ≥2 seizures without any obvious cause, starting between the ages of 3-18 years in previously healthy persons who had resided for at least 3 years in the onchocerciasis endemic area. RESULTS: Seven hundred and thirty-six PWE were included in the study; 315 (42.8%) were females; median age was 18 years. A variety of seizure types were reported: generalized tonic-clonic seizures in 511 PWE (69.4%), absences in 15 (2.0%), focal motor seizures with full awareness in 7 (1.0%), focal motor seizures with impaired awareness in 25 (3.4%), brief episodes of hallucinations in 316 (43.9%) and nodding seizures in 335 (45.5%). The median age of onset of all seizures was 10 years, and 8 years for nodding seizures. PWE with nodding seizures presented with more cognitive disabilities. The diagnostic criteria for OAE were met by 414 (85.2%) of the 486 PWE with complete information. Eighty (11.0%) PWE presented with Nakalanga features. Only 378 (51.4%) PWE were taking anti-epileptic treatment. CONCLUSION: PWE presented with a wide spectrum of seizures. The high percentage of PWE who met the diagnostic criteria for OAE suggests that better onchocerciasis control could prevent new cases. Urgent action is needed to close the anti-epileptic treatment gap.

Species interactions may help explain the erratic periodicity of whooping cough dynamics.

Incidence of whooping cough exhibits variable dynamics across time and space. The periodicity of this disease varies from annual to five years in different geographic regions in both developing and developed countries. Many hypotheses have been put forward to explain this variability such as nonlinearity and seasonality, stochasticity, variable recruitment of susceptible individuals via birth, immunization, and immune boosting. We propose an alternative hypothesis to describe the variability in periodicity - the intricate dynamical variability of whooping cough may arise from interactions between its dominant etiological agents of Bordetella pertussis and Bordetella parapertussis. We develop a two-species age-structured model, where two pathogens are allowed to interact by age-dependent convalescence of individuals with severe illness from infections. With moderate strength of interactions, the model exhibits multi-annual coexisting attractors that depend on the R0 of the two pathogens. We also examine how perturbation from case importation and noise in transmission may push the system from one dynamical regime to another. The coexistence of multi-annual cycles and the behavior of switching between attractors suggest that variable dynamics of whopping cough could be an emergent property of its multi-agent etiology.

Cross-immunity between strains explains the dynamical pattern of paramyxoviruses.

Viral respiratory tract diseases pose serious public health problems. Our ability to predict and thus, be able to prepare for outbreaks is strained by the complex factors driving the prevalence and severity of these diseases. The abundance of diseases and transmission dynamics of strains are not only affected by external factors, such as weather, but also driven by interactions among viruses mediated by human behavior and immunity. To untangle the complex out-of-phase annual and biennial pattern of three common paramyxoviruses, Respiratory Syncytial Virus (RSV), Human Parainfluenza Virus (HPIV), and Human Metapneumovirus (hMPV), we adopt a theoretical approach that integrates ecological and immunological mechanisms of disease interactions. By estimating parameters from multiyear time series of laboratory-confirmed cases from the intermountain west region of the United States and using statistical inference, we show that models of immune-mediated interactions better explain the data than those based on ecological competition by convalescence. The strength of cross-protective immunity among viruses is correlated with their genetic distance in the phylogenetic tree of the paramyxovirus family.

Role of word-of-mouth for programs of voluntary vaccination: A game-theoretic approach.

We propose a model describing the synergetic feedback between word-of-mouth (WoM) and epidemic dynamics controlled by voluntary vaccination. The key feature consists in combining a game-theoretic model for the spread of WoM and a compartmental model describing VSIR disease dynamics in the presence of a program of voluntary vaccination. We evaluate and compare two scenarios for determinants of behavior, depending on what WoM disseminates: (1) vaccine advertising, which may occur whether or not an epidemic is ongoing and (2) epidemic status, notably disease prevalence. Understanding the synergy between the two strategies could be particularly important for designing voluntary vaccination campaigns. We find that, in the initial phase of an epidemic, vaccination uptake is determined more by vaccine advertising than the epidemic status. As the epidemic progresses, epidemic status becomes increasingly important for vaccination uptake, considerably accelerating vaccination uptake toward a stable vaccination coverage.

Spatiotemporal dynamics of insect pest population under viral infection.

The interrelationship between pathogen infection and host mobility is of great importance for successful spread of disease in spatial pest population. As spread of infection depends on horizontal transmission of pathogen, there are numerous factors like susceptibility, latent period, host movement that influence overall effectiveness of the control policy. Initiation of new infection cycle depends on density of infected inoculum in the site. So, spatial movement of infected hosts during the course of infection influence the dynamics. Also, infected individuals are more vulnerable to predators and hence production of virus particles in the site depends on predation to some extent. We derive a four dimensional delayed reaction-diffusion model in one spatial dimension and compute the minimum travelling speed of transmission of infection. We show that the minimum speed is sensitive to several parameters of the system. For example, the minimum speed decreases only with increase in delay in lysis process, but otherwise it increases with increase in force of infection, diffusivity of infectives or per capita virus production. A concluding discussion with numerical simulation is presented in the end.