Mathematical modelling of parasite dynamics: a stochastic simulation-based approach and parameter estimation via modified sequential-type approximate Bayesian computation

The development of mathematical models for studying newly emerging and re-emerging infectious diseases has gained momentum due to global events. The gyrodactylid-fish system, like many host-parasite systems, serves as a valuable resource for ecological, evolutionary, and epidemiological investigations owing to its ease of experimental manipulation and long-term monitoring. Although this system has an existing individual-based model, it falls short in capturing information about species-specific microhabitat preferences and other biological details for different Gyrodactylus strains across diverse fish populations. This current study introduces a new individual-based stochastic simulation model that uses a hybrid τ-leaping algorithm to incorporate this essential data, enhancing our understanding of the complexity of the gyrodactylid-fish system. We compare the infection dynamics of three gyrodactylid strains across three host populations. A modified sequential-type approximate Bayesian computation (ABC) method, based on sequential Monte Carlo and sequential importance sampling, is developed. Additionally, we establish two penalised local-linear regression methods (based on L1 and L2 regularisations) for ABC post-processing analysis to fit our model using existing empirical data. With the support of experimental data and the fitted mathematical model, we address open biological questions for the first time and propose directions for future studies on the gyrodactylid-fish system. The adaptability of the mathematical model extends beyond the gyrodactylid-fish system to other host-parasite systems. Furthermore, the modified ABC methodologies provide efficient calibration for other multi-parameter models characterised by a large set of correlated or independent summary statistics

In silico modelling of parasite dynamics

Understanding host-parasite systems are challenging if biologists employ just the experimental approaches adopted, whereas mathematical models can help uncover other in-depth knowledge about host infection dynamics. Previous experimental studies have explored the infrapopulation dynamics of Gyrodactylus turnbulli and G. bullatarudis ectoparasites on their fish host, Poecilia reticulata. However, other important and open biological questions exist concerning parasite microhabitat preference, host survival, parasite virulence, and the transmission dynamics of different Gyrodactylus strains across different host populations over time. This thesis mathematically investigates these relevant biological questions to understand the gyrodactylid-fish system’s complexity better using a sophisticated multi-state Markov model (MSM) and a novel individual-based stochastic simulation model. The infection dynamics of three different gyrodactylid strains are compared across three different host populations. A modified approximate Bayesian computation (ABC) with sequential Monte Carlo (SMC) and sequential importance sampling (SIS) is developed for calibrating the novel stochastic model based on existing empirical data and an auxiliary stochastic model. In addition, an extended local-linear regression (with L2 regularisation) for ABC post-processing analysis has been proposed. Advanced statistics and an MSM are used to assess spatial-temporal parasite dynamics. A linear birth-death process with catastrophic extinction (B-D-C process) is considered the auxiliary model for the complex simulation model to refine the modified ABC’s summary statistics, with other theoretical justifications and parameter estimation techniques of the B-D-C process provided. The B-D-C process simulation using τ -leaping also provides additional insights on accelerating the complex simulation model by proposing a reasonable error threshold based on the trade-off between simulation accuracy and computational speed. The mathematical models can be extended and adapted for other host-parasite systems, and the modified ABC methodologies can also aid in efficiently calibrating other multi-parameter models with a high-dimensional set of correlating or independent summary statistics

Statistical modeling of HIV, tuberculosis, and Hepatitis B transmission in Ghana

Most mortality studies usually attribute death to single disease, while various other diseases could also act in the same individual or a population at large. Few works have been done by considering HIV, Tuberculosis (TB), and Hepatitis B (HB) as jointly acting in a population in spite of their high rate of infections in Ghana. This study applied competing risk methods on these three diseases by assuming they were the major risks in the study population. Among all opportunistic infections that could also act within HIV-infected individuals, TB has been asserted to be the most predominant. Other studies have also shown cases of HIV and Hepatitis B coinfections. The validity of these comorbidity assertions was statistically determined by exploring the conditional dependencies existing among HIV, TB, and HB through Bayesian networks or directed graphical model. Through Classification tree, sex and age group of individuals were found as significant demographic predictors that influence the prevalence of HIV and TB. Females were more likely to contract HIV, whereas males were prone to contracting TB

Modelling the transmission dynamics of tuberculosis in the Ashanti region of Ghana

Mathematical models can aid in elucidating the spread of infectious disease dynamics within a given population over time. In an attempt to model tuberculosis (TB) dynamics among high-burden districts in the Ashanti Region of Ghana, the SEIR epidemic model with demography was employed within both deterministic and stochastic settings for comparison purposes. The deterministic model showed success in modelling TB infection in the region to the transmission dynamics of the stochastic SEIR model over time. It predicted tuberculosis dying out in ten of twelve high-burden districts in the Ashanti Region, but an outbreak in Obuasi municipal and Amansie West district. The effect of introducing treatment at the incubation stage of TB transmission was also investigated, and it was discovered that treatment introduced at the exposed stage decreased the spread of TB. Branching process approximation was used to derive explicit forms of relevant epidemiological quantities of the deterministic SEIR model for stability analysis of equilibrium points. Numerical simulations were performed to validate the overall infection rate, basic reproductive number, herd immunity threshold, and Malthusian parameter based on bootstrapping, jackknife, and Latin Hypercube sampling schemes. It was recommended that the Ghana Health Service should find a good mechanism to detect TB in the early stages of infection in the region. Public health attention must also be given to districts with a potentially higher risk of experiencing endemic TB even though the estimates of the overall epidemic thresholds from our SEIR model suggested that the Ashanti Region as a whole had herd immunity against TB infection

Spatial and temporal parasite dynamics: microhabitat preferences and infection progression of two co-infecting gyrodactylids

Background Mathematical modelling of host-parasite systems has seen tremendous developments and broad applications in theoretical and applied ecology. The current study focuses on the infection dynamics of a gyrodactylid-fish system. Previous experimental studies have explored the infrapopulation dynamics of co-infecting ectoparasites, Gyrodactylus turnbulli and G. bullatarudis, on their fish host, Poecilia reticulata, but questions remain about parasite microhabitat preferences, host survival and parasite virulence over time. Here, we use more advanced statistics and a sophisticated mathematical model to investigate these questions based on empirical data to add to our understanding of this gyrodactylid-fish system. Methods A rank-based multivariate Kruskal-Wallis test coupled with its post-hoc tests and graphical summaries were used to investigate the spatial and temporal parasite distribution of different gyrodactylid strains across different host populations. By adapting a multi-state Markov model that extends the standard survival models, we improved previous estimates of survival probabilities. Finally, we quantified parasite virulence of three different strains as a function of host mortality and recovery across different fish stocks and sexes. Results We confirmed that the captive-bred G. turnbulli and wild G. bullatarudis strains preferred the caudal and rostral regions respectively across different fish stocks; however, the wild G. turnbulli strain changed microhabitat preference over time, indicating microhabitat preference of gyrodactylids is host and time dependent. The average time of host infection before recovery or death was between 6 and 14 days. For this gyrodactylid-fish system, a longer period of host infection led to a higher chance of host recovery. Parasite-related mortalities are host, sex and time dependent, whereas fish size is confirmed to be the key determinant of host recovery. Conclusion From existing empirical data, we provided new insights into the gyrodactylid-fish system. This study could inform the modelling of other host-parasite interactions where the entire infection history of the host is of interest by adapting multi-state Markov models. Such models are under-utilised in parasitological studies and could be expanded to estimate relevant epidemiological traits concerning parasite virulence and host survival

Mathematical modelling of parasite dynamics: A stochastic simulation-based approach and parameter estimation via modified sequential-type approximate Bayesian computation

The development of mathematical models for studying newly emerging and re-emerging infectious diseases has gained momentum due to global events. The gyrodactylid-fish system, like many host-parasite systems, serves as a valuable resource for ecological, evolutionary, and epidemiological investigations owing to its ease of experimental manipulation and long-term monitoring. Although this system has an existing individual-based model, it falls short in capturing information about species-specific microhabitat preferences and other biological details for different Gyrodactylus strains across diverse fish populations. This current study introduces a new individual-based stochastic simulation model that uses a hybrid -leaping algorithm to incorporate this essential data, enhancing our understanding of the complexity of the gyrodactylid-fish system. We compare the infection dynamics of three gyrodactylid strains across three host populations. A modified sequential-type approximate Bayesian computation (ABC) method, based on sequential Monte Carlo and sequential importance sampling, is developed. Additionally, we establish two penalised local-linear regression methods (based on L1 and L2 regularisations) for ABC post-processing analysis to fit our model using existing empirical data. With the support of experimental data and the fitted mathematical model, we address open biological questions for the first time and propose directions for future studies on the gyrodactylid-fish system. The adaptability of the mathematical model extends beyond the gyrodactylid-fish system to other host-parasite systems. Furthermore, the modified ABC methodologies provide efficient calibration for other multi-parameter models characterised by a large set of correlated or independent summary statistics

Markov chain modeling of HIV, tuberculosis, and Hepatitis B transmission in Ghana

Several mathematical and standard epidemiological models have been proposed in studying infectious disease dynamics. These models help to understand the spread of disease infections. However, most of these models are not able to estimate other relevant disease metrics such as probability of first infection and recovery as well as the expected time to infection and recovery for both susceptible and infected individuals. That is, most of the standard epidemiological models used in estimating transition probabilities (TPs) are not able to generalize the transition estimates of disease outcomes at discrete time steps for future predictions. This paper seeks to address the aforementioned problems through a discrete-time Markov chain model. Secondary datasets from cohort studies were collected on HIV, tuberculosis (TB), and hepatitis B (HB) cases from a regional hospital in Ghana. The Markov chain model revealed that hepatitis B was more infectious over time than tuberculosis and HIV even though the probability of first infection of these diseases was relatively low within the study population. However, individuals infected with HIV had comparatively lower life expectancies than those infected with tuberculosis and hepatitis B. Discrete-time Markov chain technique is recommended as viable for modeling disease dynamics in Ghana

Ethnomedicinal Survey of Plants Used for the Management of Hypertension Sold in the Makola Market, Accra, Ghana

Hypertension is a highly prevalent public health problem among Africans, including Ghanaians, and it is a major risk factor for cardiovascular diseases such as congestive heart failure, kidney disease, and coronary artery disease. Hypertension occurs at a rate of 19% to 48% across Ghana; and because about 70% of the patients are believed to be using herbs to manage this condition, it is important to know the kind of plants that are used in the management of this condition. The aim of this study was therefore to conduct an ethnomedicinal survey to document medicinal plant species which are sold on the open Ghanaian market; and are traditionally used in the treatment of hypertension. Validated questionnaires were administered to sellers of dried or semi-processed herbs at the Makola market, in the Accra Metropolitan Area. The survey identified the plant materials and the way and manner; by which these plant materials are prepared and administered. A total of 13 plant species belonging to 13 plant families were identified. The following medicinal plants were found to be commonly sold for the treatment of hypertension: Bambusa vulgaris (Graminaeae), Bridellia ferruginea (Euphorbiaceae), Carica papaya (Caricaceae), Mangifera indica (Anacardiaceae), Moringa oleifera (Moringaceae), Nauclea latifolia (Rubiaceae), Ocimum gratissimum (Lamiaceae), Parkia biglobosa (Leguminosae), Persea americana (Lauraceae), Proporis africana (Leguminosae – Mimosoideae), Pseudocedrela kotschyii (Maliaceae), Theobroma cacao (Sterculiaceae) and Vitellaria paradoxa (Sapotaceae). Leaves and roots of these plants predominated other plant parts. Most of these herbs were prepared as aqueous decoctions before administration. In conclusion, there are many medicinal plant species used to treat several conditions, including hypertension, within the Ghanaian community. This study therefore underscores the need to preserve, document and scientifically investigate traditional herbs used for the treatment of various diseases of public health importance, and to optimize their use since they serve as alternative treatment

Integration for coexistence? Implementation of intercultural health care policy in Ghana from the perspective of service users and providers

Objective In spite of the World Health Organization's recommendations over the past decades, Ghana features pluralistic rather than truly integrated medical system. Policies about the integration of complementary medicine into the national health care delivery system need to account for individual-level involvement and cultural acceptability of care rendered by health care providers. Studies in Ghana, however, have glossed over the standpoint of the persons of the illness episode about the intercultural health care policy framework. This paper explores the health care users, and providers’ experiences and attitudes towards the implementation of intercultural health care policy in Ghana. Methods In-depth interviews, augmented with informal conversations, were conducted with 16 health service users, 7 traditional healers and 6 health professionals in the Sekyere South District and Kumasi Metropolis in the Ashanti Region of Ghana. Data were thematically analysed and presented based on the a posteriori inductive reduction approach. Results Findings reveal a widespread positive attitude to, and support for integrative medical care in Ghana. However, inter-provider communication in a form of cross-referrals and collaborative mechanisms between healers and health professionals seldom occurs and remains unofficially sanctioned. Traditional healers and health care professionals are skeptical about intercultural health care policy mainly due to inadequate political commitment for provider education. The medical practitioners have limited opportunity to undergo training for integrative medical practice. We also find a serious mistrust between the practitioners due to the “diversity of healing approaches and techniques.” Weak institutional support, lack of training to meet standards of practice, poor registration and regulatory measures as well as negative perception of the integrative medical policy inhibit its implementation in Ghana. Conclusion In order to advance any useful intercultural health care policy in Ghana, the government's total commitment in informed training and provider education, enforcement of regulatory instrument and improved community engagement is needed. Evidence-based incorporation of traditional medical therapies into clinical practice will provide safer, faster and more effective health care for the underserved and resource-poor, particularly in the rural areas.</p