Variable effect of co-infection on the HIV infectivity: within-host dynamics and epidemiological significance

Uncovering HIV and malaria interactions: the latest evidence and knowledge gaps

The geographical distribution of malaria and HIV infections widely overlap in sub-Saharan Africa, constituting a complex global health challenge. The interplay between both infections raises concerns about potential immunological, clinical, and therapeutic interactions. Both diseases have been reported to exacerbate the transmission of the other, including the possible vertical transmission of HIV in pregnant individuals with malaria. Co-infection also increases the risk of adverse outcomes such as severe malaria and death. In addition, interactions between antiretroviral and antimalarial drugs have been reported, potentially reducing the efficacy of these drugs. We review the current knowledge of the epidemiological, clinical, immunological, and therapeutic interactions of both infections. We focus on the latest available data and identify key knowledge gaps that should be addressed to guide policy makers in providing optimal HIV and malaria prevention, care, and treatment in vulnerable populations.

A Network Immuno-Epidemiological HIV Model

In this paper we formulate a multi-scale nested immuno-epidemiological model of HIV on complex networks. The system is described by ordinary differential equations coupled with a partial differential equation. First, we prove the existence and uniqueness of the immunological model and then establish the well-posedness of the multi-scale model. We derive an explicit expression of the basic reproduction number [Formula: see text] of the immuno-epidemiological model. The system has a disease-free equilibrium and an endemic equilibrium. The disease-free equilibrium is globally stable when [Formula: see text] and unstable when [Formula: see text]. Numerical simulations suggest that [Formula: see text] increases as the number of nodes in the network increases. Further, we find that for a scale-free network the number of infected individuals at equilibrium is a hump-like function of the within-host reproduction number; however, the dependence becomes monotone if the network has predominantly low connectivity nodes or high connectivity nodes.

Impact of Endemic Infections on HIV Susceptibility in Sub-Saharan Africa

Human immunodeficiency virus (HIV) remains a leading cause of global morbidity with the highest burden in Sub-Saharan Africa (SSA). For reasons that are incompletely understood, the likelihood of HIV transmission is several fold higher in SSA than in higher income countries, and most of these infections are acquired by young women. Residents of SSA are also exposed to a variety of endemic infections, such as malaria and various helminthiases that could influence mucosal and systemic immunology. Since these immune parameters are important determinants of HIV acquisition and progression, this review explores the possible effects of endemic infections on HIV susceptibility and summarizes current knowledge of the epidemiology and underlying immunological mechanisms by which endemic infections could impact HIV acquisition. A better understanding of the interaction between endemic infections and HIV may enhance HIV prevention programs in SSA.

HIV Reverse Transcriptase and Protease Genes Variability Can Be a Biomarker Associated with HIV and Hepatitis B or C Coinfection

Variability of the HIV reverse transcriptase (RT) and protease (PR) genes has been used as indicators of drug resistance and as a mean to evaluate phylogenetic relationships among circulating virus. However, these studies have been carried in HIV mono-infected populations. The goal of this study was to evaluate, for the first time, the HIV PR and RT sequences from HIV/HBV and HIV/HCV co-infected patients. HIV PR and RT genes were amplificated and sequenced to resistance analysis. The bioinformatics analysis was performed to infer about sequences clustering and molecular evolution. The results showed that the most frequent amino acid substitutions in RT were L214F (67.6%), I135T (55.9%), and in PR was V15I (41.2%). The molecular clock analysis showed that the HIV circulating in co-infected patients were separated in two clusters in the years 1999-2000. Some patients included as HIV mono-infected according patients' medical records and inside the co-infected cluster were, in fact, co-infected by PCR analysis. Analysis of the decision trees showed susceptibility to lamivudine and emtricitabine were important attribute to characterize co-infected patients. In conclusion, the results obtained in this study suggest, for the first time, that HIV RT and PR genes variability could be a genetic biomarker to coinfection.

Multi-scale immunoepidemiological modeling of within-host and between-host HIV dynamics: systematic review of mathematical models

OBJECTIVE

The objective of this study is to conduct a systematic review of multi-scale HIV immunoepidemiological models to improve our understanding of the synergistic impact between the HIV viral-immune dynamics at the individual level and HIV transmission dynamics at the population level.

BACKGROUND

While within-host and between-host models of HIV dynamics have been well studied at a single scale, connecting the immunological and epidemiological scales through multi-scale models is an emerging method to infer the synergistic dynamics of HIV at the individual and population levels.

METHODS

We reviewed nine articles using the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) framework that focused on the synergistic dynamics of HIV immunoepidemiological models at the individual and population levels.

RESULTS

HIV immunoepidemiological models simulate viral immune dynamics at the within-host scale and the epidemiological transmission dynamics at the between-host scale. They account for longitudinal changes in the immune viral dynamics of HIV+ individuals, and their corresponding impact on the transmission dynamics in the population. They are useful to analyze the dynamics of HIV super-infection, co-infection, drug resistance, evolution, and treatment in HIV+ individuals, and their impact on the epidemic pathways in the population. We illustrate the coupling mechanisms of the within-host and between-host scales, their mathematical implementation, and the clinical and public health problems that are appropriate for analysis using HIV immunoepidemiological models.

CONCLUSION

HIV immunoepidemiological models connect the within-host immune dynamics at the individual level and the epidemiological transmission dynamics at the population level. While multi-scale models add complexity over a single-scale model, they account for the time varying immune viral response of HIV+ individuals, and the corresponding impact on the time-varying risk of transmission of HIV+ individuals to other susceptibles in the population.

Competitive exclusion in a multi-strain immuno-epidemiological influenza model with environmental transmission

In this paper, a multi-strain model that links immunological and epidemiological dynamics across scales is formulated. On the within-host scale, the n strains eliminate each other with the strain having the largest immunological reproduction number persisting. However, on the population scale, we extend the competitive exclusion principle to a multi-strain model of SI-type for the dynamics of highly pathogenic flu in poultry that incorporates both the infection age of infectious individuals and biological age of pathogen in the environment. The two models are linked through the age-since-infection structure of the epidemiological variables. In addition the between-host transmission rate, the shedding rate of individuals infected by strain j and the disease-induced death rate depend on the within-host viral load. The immunological reproduction numbers [Formula: see text] and the epidemiological reproduction numbers [Formula: see text] are computed. By constructing a suitable Lyapunov function, the global stability of the infection-free equilibrium in the system is obtained if all reproduction numbers are smaller or equal to one. If [Formula: see text], the reproduction number of strain j is larger than one, then a single-strain equilibrium, corresponding to strain j exists. This single-strain equilibrium is globally stable whenever [Formula: see text] and [Formula: see text] is the unique maximal reproduction number and all of the reproduction numbers are distinct. That is, the strain with the maximal basic reproduction number competitively excludes all other strains.

Brief report: HIV-1 transmissions during asymptomatic infection: exploring the impact of changes in HIV-1 viral load due to coinfections

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High HIV-1 plasma viral loads (PVLs) in sub-Saharan Africa, partly because of high rates of coinfection, may have been one of the drivers of the “explosive” epidemics seen in that region. Using a previously published framework of infectiousness and survival, we estimate the excess onward HIV-1 transmission events (secondary infections) resulting from coinfection-induced changes in PVL during asymptomatic HIV-1 infection. For every 100 HIV-infected people, each suffering 1 episode of tuberculosis infection, there are 4.9 (2.7th–97.5th percentile: 0.2–21.5) excess onward HIV-1 transmission events attributable to this coinfection. Other estimates are malaria 0.4 (0.0–2.0), soil-transmitted helminths 3.1 (0.1–14.9), schistosomiasis 8.5 (0.2–38.6), filariasis 13.3 (0.3–89.2), syphilis 0.1 (0.0–1.6), herpes simplex virus 4.0 (0.0–24.2), and gonorrhea 2.1 (0.1–8.0) transmissions. If these higher PVLs confer a shorter life expectancy and higher infectiousness, then their impact on transmission is, in general, reduced. For most HIV-1 coinfections, the duration of a single infection is too short and/or the associated PVL elevation is too modest to contribute substantially to onward HIV-1 transmission.

Determining parameter distribution in within-host severe P. falciparum malaria

Numerous studies have been carried out on within-host Plasmodium falciparum malaria with varying results. Some studies have suggested over estimation of parasite growth within an infected host while others stated that evolution of parasitaemia seems to be quelled by parasite load. Various mathematical models have been designed to understand the dynamics of evolution of within-host malaria. The basic ingredient in most of the models is that the availability of uninfected red blood cells (RBCs) in which the parasite develops is a limiting factor in the propagation of the parasite population. We hypothesize that in severe malaria, due to parasite quest for survival and rapid multiplication, the vicious malaria parasite is sophisticated and can be absorbed in an already infected RBC and speeds up rapture rate. The study reviews the classical models of blood stage malaria and proposes a new model which incorporates double infection. Analysis of the model and parameter identifiability using Markov chain Monte Carlo (MCMC) are presented. MCMC uses distribution of parameters to study the model behavior instead of single points. Results indicate that most infected RBCs rupture quickly due to the disease instead. This may explain anemia in malaria patients and lack of uniformity of oscillations in within-host malaria. Therefore, more needs to be done as far as within-host malaria is concerned, to provide step by step evolution of malaria within a host.

Linking immunological and epidemiological dynamics of HIV: the case of super-infection

In this paper, a two-strain model that links immunological and epidemiological dynamics across scales is formulated. On the within-host scale, the two strains eliminate each other with the strain with the larger immunological reproduction persisting. However, on the population scale superinfection is possible, with the strain with larger immunological reproduction number super-infecting the strain with the smaller immunological reproduction number. The two models are linked through the age-since-infection structure of the epidemiological variables. In addition, the between-host transmission and the disease-induced death rate depend on the within-host viral load. The immunological reproduction numbers, the epidemiological reproduction numbers and invasion reproduction numbers are computed. Besides the disease-free equilibrium, there are two population-level strain one and strain two isolated equilibria, as well as a population-level coexistence equilibrium when both invasion reproduction numbers are greater than one. The single-strain population-level equilibria are locally asymptotically stable suggesting that in the absence of superinfection oscillations do not occur, a result contrasting previous studies of HIV age-since-infection structured models. Simulations suggest that the epidemiological reproduction number and HIV population prevalence are monotone functions of the within-host parameters with reciprocal trends. In particular, HIV medications that decrease within-host viral load also increase overall population prevalence. The effect of the immunological parameters on the population reproduction number and prevalence is more pronounced when the initial viral load is lower.