Coinfection of vector borne disease: consequences for individuals and populations.

Global elimination efforts against lymphatic filariasis have made significant progress in reducing the prevalence and intensity of filarial worms around the world. In addition, malaria control and elimination efforts are achieving regional successes in protecting millions of people from illness. However, the causative pathogens of these diseases are part of larger ecosystems, within the host, and within the vector. During infection of a host or vector, direct, or indirect, interactions between these and other pathogens may have important consequences for transmission dynamics at the population level. For example, laboratory co-infection with filariasis reduces the potential for malaria transmission, likely due to the immune priming effect of large filarial worms within the mosquito. Conversely, the passage of large worms through the mosquito could aid the dissemination or viruses, thereby increasing the potential for transmission. The wider effects of successfully eliminating one pathogen from a complex system has not been thoroughly explored.

This project will use experimental infections of mosquitoes with filarial worms, malaria and/or arboviruses to determine whether co-infection (either synchronous or sequential) influences the transmission of single pathogens.

The epidemiological significance of co-infections, and the effect of the elimination of one pathogen on the transmission of another, will be explored through mechanistic models of vector-borne disease transmission, informed from the results of infection experiments.

T2 Human / Clinical Research

T1 – Basic Research and T4 Practice to Policy / Population

Expected Outputs

This project will lead to high quality publications and presentations to international consortia and conferences.

The student will generate data to support grant applications on transmission dynamics using our experimental infection system.

Training Opportunities

Working at Containment Level 3

Statistical and dynamical modelling

Skills Required

Degree in biological sciences

Key Publications associated with this project

Irvine MA, Kazura JW, Hollingsworth TD, Reimer LJ. Understanding heterogeneities in mosquito bite exposure and infection distributions for the elimination of lymphatic filariasis. Proc Biol Sci 2018 doi: 10.1098/rspb.2017.2253

Davis EL, Reimer LJ, Pellis L, Hollingsworth TD. Evaluating the evidence for lymphatic filariasis elimination Trends Parasitol. 2019 Nov;35(11):860-869. DOI: 10.1016/j.pt.2019.08.003

Erickson SM, Thomsen EK, Keven JB, Vincent N, Koimbu G, Siba PM, Christensen BM, Reimer LJ. Mosquito-parasite interactions can shape filariasis transmission dynamics and impact elimination programs. PLoS NTD 2013 7(9): e2433.

Slater HC, Gambhir M, Parham PE, Michael E. Modelling co-infection with malaria and lymphatic filariasis. PLoS Comput Biol 2013 doi: 10.1371/journal.pcbi.1003096

LSTM Themes and Topics – Key Words

Vector Biology

Neglected Tropical Diseases

Malaria and other Vector Borne Diseases