Modeling malaria and typhoid fever co-infection dynamics

Modeling measles transmission in adults and children: Implications to vaccination for eradication

Despite the availability of successful vaccines, measles outbreaks have occurred frequently in recent years, presumably due to the lack of proper vaccination implementation. Moreover, measles cases in adult groups, albeit small in number, indicate that the previously neglected adult group may need to be brought into vaccine coverage to achieve WHO's goal of measles eradication from the globe. In this study, we develop a novel transmission dynamics model to describe measles cases in adults and children to evaluate the role of adult infection in persistent measles cases and vaccination programs for eradication. Analysis of our model, validated by measles cases from outbreaks in Nepal, provides the vaccination reproduction number (conditions for measles eradication or persistence) and the role of contact network size. Our results highlight that while children are primary targets for measles outbreaks, a small number of infections in adults may act as a reservoir for measles, causing obstacles to eradication. Furthermore, our model analysis shows that while impactful controls can be achieved by children-focused vaccines, a combined adult-child vaccination program may help assert eradication of the disease.

Modeling and investigating malaria P. Falciparum and P. Vivax infections: Application to Djibouti data

Malaria is an infectious and communicable disease, caused by one or more species of Plasmodium parasites. There are five species of parasites responsible for malaria in humans, of which two, Plasmodium Falciparum and Plasmodium Vivax, are the most dangerous. In Djibouti, the two species of Plasmodium are present in different proportions in the infected population: 77% of P. Falciparum and 33% of P. Vivax. In this study we present a new mathematical model describing the temporal dynamics of Plasmodium Falciparum and Plasmodium Vivax co-infection. We focus briefly on the well posedness of this model and on the calculation of the basic reproductive numbers for the infections with each Plasmodium species that help us understand the long-term dynamics of this model (i.e., existence and stability of various eqiuilibria). Then we use computational approaches to: (a) identify model parameters using real data on malaria infections in Djibouti; (b) illustrate the influence of different estimated parameters on the basic reproduction numbers; (c) perform global sensitivity and uncertainty analysis for the impact of various model parameters on the transient dynamics of infectious mosquitoes and infected humans, for infections with each of the Plasmodium species. The originality of this research stems from employing the FAST method and the LHS method to identify the key factors influencing the progression of the disease within the population of Djibouti. In addition, sensitivity analysis identified the most influential parameter for Falciparium and Vivax reproduction rates. Finally, the uncertainty analysis enabled us to understand the variability of certain parameters on the infected compartments.

Indirect interaction between an endemic and an invading pathogen: A case study of Plasmodium and Usutu virus dynamics in a shared bird host population

Infectious disease agents can influence each other's dynamics in shared host populations. We consider such influence for two mosquito-borne infections where one pathogen is endemic at the time that a second pathogen invades. We regard a setting where the vector has a bias towards biting host individuals infected with the endemic pathogen and where there is a cost to co-infected hosts. As a motivating case study, we regard Plasmodium spp., that cause avian malaria, as the endemic pathogen, and Usutu virus (USUV) as the invading pathogen. Hosts with malaria attract more mosquitoes compared to susceptible hosts, a phenomenon named vector bias. The possible trade-off between the vector-bias effect and the co-infection mortality is studied using a compartmental epidemic model. We focus first on the basic reproduction number R0 for Usutu virus invading into a malaria-endemic population, and then explore the long-term dynamics of both pathogens once Usutu virus has become established. We find that the vector bias facilitates the introduction of malaria into a susceptible population, as well as the introduction of Usutu in a malaria-endemic population. In the long term, however, both a vector bias and co-infection mortality lead to a decrease in the number of individuals infected with either pathogen, suggesting that avian malaria is unlikely to be a promoter of Usutu invasion. This proposed approach is general and allows for new insights into other negative associations between endemic and invading vector-borne pathogens.

Magnitude of Malaria-Typhoid Fever Coinfection in Febrile Patients at Arba Minch General Hospital in Southern Ethiopia

BACKGROUND

Coinfection with malaria and typhoid fever is a major public health issue in developing countries. In endemic areas, including Ethiopia, people are at risk of acquiring both malaria and typhoid fever at the same time. Therefore, this study aimed to determine the magnitude of malaria-typhoid fever coinfection in febrile patients attending hospital at Southern Ethiopia.

METHODS

A hospital-based cross-sectional study was carried out on 416 febrile patients attending Arba Minch General Hospital from 1st October to 30th December 2021. The data was collected using a pretested structured questionnaire. Capillary and Venus blood samples were collected for assessing malaria and typhoid fever, respectively. Blood smear, culture, and biochemical tests were performed based on standard parasitological and microbiological methods. The P-value ≤ 0.05 was considered statistically significant.

RESULTS

The magnitude of malaria, typhoid fever, and their coinfections was 26.2% (109/416), 6.5% (27/416), and 3.1% (13/416), respectively. Among the confirmed malaria cases, about 66% of infections were Plasmodium falciparum. The malaria-typhoid fever coinfection showed a statistically significant association with a clinical presentation of a continuous pattern of fever (AOR = 5.84; 95% CI: 1.44-23.71, P = 0.014) and chills (AOR = 3.94; 95% CI: 1.04-14.89, P = 0.044). About 29.6% of Salmonella isolates were multidrug-resistant (MDR).

CONCLUSION

The total rate of coinfection with malaria and typhoid fever was comparable to that of previous studies. With the consideration of higher prevalence of drug resistance of Salmonella spp. and higher prevalence of malaria-typhoid fever coinfection, proper diagnostic procedure should be implemented for proper use of drugs.

Mathematical Models for Typhoid Disease Transmission: A Systematic Literature Review

Explaining all published articles on the typhoid disease transmission model was carried out. It has been conducted to understand how Salmonella is transmitted among humans and vectors with variation interventions to control the spread of the typhoid disease. Specific objectives were to (1) identify the model developed, (2) describe the studies, and (3) identify the interventions of the model. It systemically searched and reviewed Dimension, Scopus, and ScienceDirect databases from 2013 through to 2022 for articles that studied the spread of typhoid fever through a compartmental mathematical model. This study obtained 111 unique articles from three databases, resulting in 23 articles corresponding to the created terms. All the articles were elaborated on to identify their identities for more explanation. Various interventions were considered in the model of each article, are identified, and then summarized to find out the opportunities for model development in future works. The whole article’s content was identified and outlined regarding how mathematics plays a role in model analysis and study of typhoid disease spread with various interventions. The study of mathematical modeling for typhoid disease transmission can be developed on analysis and creating the model with direct and indirect interventions to the human population for further work.

Modeling transmission dynamics of measles in Nepal and its control with monitored vaccination program

Measles is one of the highly contagious human viral diseases. Despite the availability of vaccines, measles outbreak frequently occurs in many places, including Nepal, partly due to the lack of compliance with vaccination. In this study, we develop a novel transmission dynamics model to evaluate the effects of monitored vaccination programs to control and eliminate measles. We use our model, parameterized with the data from the measles outbreak in Nepal, to calculate the vaccinated reproduction number, $ R_v $, of measles in Nepal. We perform model analyses to establish the global asymptotic stability of the disease-free equilibrium point for $ R_v < 1 $ and the uniform persistence of the disease for $ R_v > 1 $. Moreover, we perform model simulations to identify monitored vaccination strategies for the successful control of measles in Nepal. Our model predicts that the monitored vaccination programs can help control the potential resurgence of the disease.

Lymphocyte crosstalk is required for monocyte-intrinsic trained immunity to Plasmodium falciparum

Plasmodium falciparum (P. falciparum) induces trained innate immune responses in vitro, where initial stimulation of adherent PBMCs with P. falciparum-infected RBCs (iRBCs) results in hyperresponsiveness to subsequent ligation of TLR2. This response correlates with the presence of T and B lymphocytes in adherent PBMCs, suggesting that innate immune training is partially due to adaptive immunity. We found that T cell-depleted PBMCs and purified monocytes alone did not elicit hyperproduction of IL-6 and TNF-α under training conditions. Analysis of P. falciparum-trained PBMCs showed that DCs did not develop under control conditions, and IL-6 and TNF-α were primarily produced by monocytes and DCs. Transwell experiments isolating purified monocytes from either PBMCs or purified CD4+ T cells, but allowing diffusion of secreted proteins, enabled monocytes trained with iRBCs to hyperproduce IL-6 and TNF-α after TLR restimulation. Purified monocytes stimulated with IFN-γ hyperproduced IL-6 and TNF-α, whereas blockade of IFN-γ in P. falciparum-trained PBMCs inhibited trained responses. Assay for transposase-accessible chromatin with high-throughput sequencing (ATAC-Seq) on monocytes from patients with malaria showed persistently open chromatin at genes that appeared to be trained in vitro. Together, these findings indicate that the trained immune response of monocytes to P. falciparum is not completely cell intrinsic but depends on soluble signals from lymphocytes.

MODELING THE ROLE OF VACCINATION, ENVIRONMENTAL SANITATION, AND SATURATED TREATMENT ON THE SPREAD OF TYPHOID FEVER

A deterministic nonlinear mathematical model is developed for typhoid transmission dynamics in human hosts, coupled with multiple transmission routes. The model aims to examine the role of control interventions such as vaccination, environmental sanitation, and saturated treatment on the prevalence of typhoid. First, the qualitative analysis of the model with constant control interventions is performed. The model exhibits a backward bifurcation phenomenon. Sensitivity analysis is also conducted to identify impactful parameters for effective control of the disease. Then, the model is extended to a corresponding optimal control problem to investigate the optimum intervention strategies by assessing their effects on typhoid prevalence and economic load. The characterization of the optimal controls is determined using Pontryagin’s Maximum Principle, and the optimality system is developed. Numerical results suggest that, in the absence of treatment, the combination of vaccination and environmental sanitation controls plays an important role in reducing the typhoid burden and economic load. Moreover, the comprehensive use of the three control interventions is more effective than using any single or two combined control interventions. It reduces the number of infective humans and environmental bacteria as well as the cost burden associated with applied controls and opportunity loss. Thus, the comprehensive effect of the three control interventions is found to be more economical during typhoid outbreaks.

Modelling the risk of HIV infection for drug abusers

Drugs of abuse, such as opiates, are one of the leading causes for transmission of HIV in many parts of the world. Drug abusers often face a higher risk of acquiring HIV because target cell (CD4+ T-cell) receptor expression differs in response to morphine, a metabolite of common opiates. In this study, we use a viral dynamics model that incorporates the T-cell expression difference to formulate the probability of infection among drug abusers. We quantify how the risk of infection is exacerbated in morphine conditioning, depending on the timings of morphine intake and virus exposure. With in-depth understanding of the viral dynamics and the increased risk for these individuals, we further evaluate how preventive therapies, including pre- and post-exposure prophylaxis, affect the infection risk in drug abusers. These results are useful to devise ideal treatment protocols to combat the several obstacles those under drugs of abuse face.

Classification of Salmonella enterica of the (Para-)Typhoid Fever Group by Fourier-Transform Infrared (FTIR) Spectroscopy

Typhoidal and para-typhoidal Salmonella are major causes of bacteraemia in resource-limited countries. Diagnostic alternatives to laborious and resource-demanding serotyping are essential. Fourier transform infrared spectroscopy (FTIRS) is a rapidly developing and simple bacterial typing technology. In this study, we assessed the discriminatory power of the FTIRS-based IR Biotyper (Bruker Daltonik GmbH, Bremen, Germany), for the rapid and reliable identification of biochemically confirmed typhoid and paratyphoid fever-associated Salmonella isolates. In total, 359 isolates, comprising 30 S. Typhi, 23 S. Paratyphi A, 23 S. Paratyphi B, and 7 S. Paratyphi C, respectively and other phylogenetically closely related Salmonella serovars belonging to the serogroups O:2, O:4, O:7 and O:9 were tested. The strains were derived from clinical, environmental and food samples collected at different European sites. Applying artificial neural networks, specific automated classifiers were built to discriminate typhoidal serovars from non-typhoidal serovars within each of the four serogroups. The accuracy of the classifiers was 99.9%, 87.0%, 99.5% and 99.0% for Salmonella Typhi, Salmonella Paratyphi A, B and Salmonella Paratyphi C, respectively. The IR Biotyper is a promising tool for fast and reliable detection of typhoidal Salmonella. Hence, IR biotyping may serve as a suitable alternative to conventional approaches for surveillance and diagnostic purposes.

High endemic levels of typhoid fever in rural areas of Ghana may stem from optimal voluntary vaccination behaviour

Typhoid fever has long established itself endemically in rural Ghana despite the availability of cheap and effective vaccines. We used a game-theoretic model to investigate whether the low vaccination coverage in Ghana could be attributed to rational human behaviour. We adopted a version of an epidemiological model of typhoid fever dynamics, which accounted not only for chronic life-long carriers but also for a short-cycle transmission in the immediate environment and a long-cycle transmission via contamination of the water supply. We calibrated the model parameters based on the known incidence data. We found that unless the (perceived) cost of vaccination is negligible, the individually optimal population vaccination rate falls significantly short of the societally optimal population vaccination rate needed to reach herd immunity. We expressed both the herd immunity and the optimal equilibrium vaccination rates in terms of only a few observable parameters such as the incidence rate, demographics, vaccine waning rate and the perceived cost of vaccination relative to the cost of infection. This allowed us not to rely on other uncertain epidemiological model parameters and, in particular, to bypass uncertainties about the role of the carriers in the transmission.

Early Economic Evaluation to Identify the Necessary Test Characteristics of a New Typhoid Test to be Cost Effective in Ghana

BACKGROUND

In Ghana, there are issues with the diagnosis of typhoid fever; these include delays in diagnosis, concerns about the accuracy of current tests, and lack of availability. These issues highlight the need for the development of a rapid, accurate, and easily accessible diagnostic test. The aim of this study was to conduct an early economic analysis of a hypothetical rapid test for typhoid fever diagnosis in Ghana and identify the necessary characteristics of the test for it to be cost effective in Ghana.

METHODS

An early cost-utility analysis was conducted using a decision tree parameterized with secondary data sources, with reasonable assumptions made for unknown parameters. The patient population considered is individuals presenting with symptoms suggestive of typhoid fever at a healthcare facility in Ghana; a time horizon of 180 days and the Ghanaian national health service perspective were adopted for the analysis. Extensive sensitivity analysis was undertaken, including headroom analysis.

RESULTS

The results here show that for a hypothetical test to perform better than the existing test (Widal) in terms of QALYs gained and cost effectiveness, it is necessary for it to have a high specificity (at least 70%) and should not be priced more than US$4. The overall value of conducting research to reduce uncertainty (over 5 years) is US$3287.

CONCLUSION

The analysis shows the potential for the hypothetical test to replace the Widal test and the market potential of developing a new test in the Ghanaian setting.

Modeling Zika Virus Transmission Dynamics: Parameter Estimates, Disease Characteristics, and Prevention

Because of limited data, much remains uncertain about parameters related to transmission dynamics of Zika virus (ZIKV). Estimating a large number of parameters from the limited information in data may not provide useful knowledge about the ZIKV. Here, we developed a method that utilizes a mathematical model of ZIKV dynamics and the complex-step derivative approximation technique to identify parameters that can be estimated from the available data. Applying our method to epidemic data from the ZIKV outbreaks in French Polynesia and Yap Island, we identified the parameters that can be estimated from these island data. Our results suggest that the parameters that can be estimated from a given data set, as well as the estimated values of those parameters, vary from Island to Island. Our method allowed us to estimate some ZIKV-related parameters with reasonable confidence intervals. We also computed the basic reproduction number to be from 2.03 to 3.20 across islands. Furthermore, using our model, we evaluated potential prevention strategies and found that peak prevalence can be reduced to nearly 10% by reducing mosquito-to-human contact by at least 60% or increasing mosquito death by at least a factor of three of the base case. With these preventions, the final outbreak-size is predicted to be negligible, thereby successfully controlling ZIKV epidemics.

Modeling co-infection of Ixodes tick-borne pathogens

Ticks, including the Ixodes ricinus and Ixodes scapularis hard tick species, are regarded as the most common arthropod vectors of both human and animal diseases in Europe and the United States capable of transmitting a large number of bacteria, viruses and parasites. Since ticks in larval and nymphal stages share the same host community which can harbor multiple pathogens, they may be co-infected with two or more pathogens, with a subsequent high likelihood of co-transmission to humans or animals. This paper is devoted to the modeling of co-infection of tick-borne pathogens, with special focus on the co-infection of Borrelia burgdorferi (agent of Lyme disease) and Babesia microti (agent of human babesiosis). Considering the effect of co-infection, we illustrate that co-infection with B. burgdorferi increases the likelihood of B. microti transmission, by increasing the basic reproduction number of B. microti below the threshold smaller than one to be possibly above the threshold for persistence. The study confirms a mechanism of the ecological fitness paradox, the establishment of B. microti which has weak fitness (basic reproduction number less than one). Furthermore, co-infection could facilitate range expansion of both pathogens.

Best practice assessment of disease modelling for infectious disease outbreaks

During emerging disease outbreaks, public health, emergency management officials and decision-makers increasingly rely on epidemiological models to forecast outbreak progression and determine the best response to health crisis needs. Outbreak response strategies derived from such modelling may include pharmaceutical distribution, immunisation campaigns, social distancing, prophylactic pharmaceuticals, medical care, bed surge, security and other requirements. Infectious disease modelling estimates are unavoidably subject to multiple interpretations, and full understanding of a model's limitations may be lost when provided from the disease modeller to public health practitioner to government policymaker. We review epidemiological models created for diseases which are of greatest concern for public health protection. Such diseases, whether transmitted from person-to-person (Ebola, influenza, smallpox), via direct exposure (anthrax), or food and waterborne exposure (cholera, typhoid) may cause severe illness and death in a large population. We examine disease-specific models to determine best practices characterising infectious disease outbreaks and facilitating emergency response and implementation of public health policy and disease control measures.

Assessing the potential impact of limited public health resources on the spread and control of typhoid

Typhoid fever is a systemic infection caused by Salmonella Typhi and occurs predominantly in association with poor sanitation and lack of clean drinking water. Despite recent progress in water and sanitation coverage, the disease remains a substantial public health problem in many developing countries. A mathematical model for the spread of typhoid has been formulated using non linear ordinary differential equations. The model includes a special treatment function to assess the effects of limited treatment resources on the spread of typhoid. It is shown that the model has multiple equilibria and using the center manifold theory, the model exhibits the phenomenon of backward bifurcation whose implications are discussed. The results suggest the need for comprehensive and accessible treatment facilities to curtail typhoid infection.

Modeling Lyme disease transmission

Lyme disease, a typical tick-borne disease, imposes increasing global public health challenges. A growing body of theoretical models have been proposed to better understand various factors determining the disease risk, which not only enrich our understanding on the ecological cycle of disease transmission but also promote new theoretical developments on model formulation, analysis and simulation. In this paper, we provide a review about the models and results we have obtained recently on modeling and analyzing Lyme disease transmission, with the purpose to highlight various aspects in the ecological cycle of disease transmission to be incorporated, including the growth of ticks with different stages in the life cycle, the seasonality, host diversity, spatial disease pattern due to host short distance movement and bird migration, co-infection with other tick-borne pathogens, and climate change impact.