In this paper, mathematical models have been employed to investigate the effectiveness of a fungal pathogen that blocks malaria transmission in mosquitoes to reduce malaria prevalence in humans. Unsurprisingly, all models indicate that malaria prevalence in humans could be reduced substantially by such a counter measure, and that the mosquito exposure rate to the fungus should be maximized to reduce malaria prevalence. However, the main interest of the results is to demonstrate that the optimal design of an agent that can simultaneously kill mosquitoes, and malaria parasites within mosquitoes depends quite sensitively on the details of a complex ecological system.
The first model, in which competition between mosquitoes occurred at the adult level, showed that in fast growing mosquito populations the fungal pathogen should be engineered to have low virulence. This result is independent of the possibility of mosquito resistance developing to the fungal pathogen and can be understood in very simple terms: fungus‐infected mosquitoes do not directly contribute to the malaria epidemic, but competitively hamper the introduction/survival of new susceptible mosquitoes. If mosquito resistance to fungal biopesticides arises in the field, this argument would additionally be strengthened.
In the second model, competition occurs at the larval stage of development. This model predicted that, in the absence of vertical transmission of the fungal pathogen, a highly virulent (biopesticidal) fungus would be desirable. However, the addition of reliable vertical transmission to this model significantly alters the predictions. If the fungal pathogen could be engineered in this way, then a high virulence would be highly detrimental to its efficacy as an anti‐malarial strategy.
The key observation that should be drawn is that finding the optimal properties of agents that can reduce the malaria parasite incidence in mosquitoes is not an easy task, since several direct and indirect effects need to be parameterized and balanced, leading to conclusions that depend on the details of the mosquito population, fungal pathogen, and environment.
In order to obtain a straightforward analytical treatment, several simplifying assumptions were made throughout. It was assumed that the fungus could completely block onward malaria transmission. Modifying this assumption in the simplified model leads to an increased favourability of virulence, but the authors believe that this issue will best be resolved in a future model where the time dependence of the fungus‐mosquito interaction is explicitly analysed. Also, by assuming a constant mass‐action biting coefficient, human reactions to avoid mosquito bites (bed nets or indoor residual spraying) were neglected. This was done to study the pure effect of the fungus interaction, but is likely not a realistic representation of a real‐life setting. Furthermore, the human population was modelled as a homogeneous population, neglecting for example co‐infections, age structure, and previous malaria history. All of the above have an important impact on the malaria epidemic: co‐infections increase the severity of each disease, children are much more vulnerable to malaria, and previous malaria infections can lead to temporal immunity. The incubation period of the malaria parasite and of the fungus in mosquitos were also neglected. This simplification particularly affects the mosquito population, where the incubation period is of about the same order as the life expectancy. Future work will include extending the current model to add more details of mosquito and malaria parasite life history in an age‐ and life‐stage‐dependent model of the mosquito.
Horizontal fungal transfer between mosquitoes was also not considered here. This effect has been observed for a number of fungal symbionts of insects and could play a role similar to vertical transmission in enhancing the effectiveness of the fungal pathogen. Horizontal transfer (possibly mediated through the environment) between mosquitoes would also be expected to increase the effectiveness of fungal spread, and reduce the necessary level of fungal application/spraying in the environment, which might otherwise have to be very intense. Further, in assuming a fairly simple logistic growth model, seasonal effects such as rainfall and humidity were neglected. These effects would lead to temporal variations in the mosquito population growth rate and carrying capacity, as well as unknown possible effects on the fungal pathogen. A final topic for possible future work is to consider spatial heterogeneities such as breeding sites and human habitat.
Despite these limitations, the models are useful in defining an argument for a minimal virulence of the antimalarial fungal pathogens. In future work, as field studies of Metarhizium or similar agents are completed, the parameterization of the model can be improved, and new models that allow insights into the potential of a large‐scale deployment of such controls for malaria and other mosquito‐borne diseases can be developed.