On the necessity of accounting for age structure in human malaria transmission modeling

• Published in: Mathematical biosciences 2024-12, Vol.378, p.109319, Article 109319
• Main Authors: Richard, Quentin, Choisy, Marc, Lefèvre, Thierry, Djidjou-Demasse, Ramsès
• Format: Article
• Language: English
• Subjects: Age Factors; Age-structured models; Analysis of PDEs; Animals; Culicidae - parasitology; Epidemiological Models; Epidemiology; Humans; Life Sciences; Malaria - epidemiology; Malaria - transmission; Malaria modeling; Mathematics; Models, Biological; Mosquito survival; Mosquito Vectors - parasitology; Santé publique et épidémiologie; Vector-borne diseases
• ISSN: 0025-5564; 1879-3134; 1879-3134
• DOI: 10.1016/j.mbs.2024.109319

Malaria is one of the most common mosquito-borne diseases widespread in tropical and subtropical regions, causing thousands of deaths every year in the world. In a previous paper, we formulated an age-structured model containing three structural variables: (i) the chronological age of human and mosquito populations, (ii) the time since they are infected, and (iii) humans waning immunity (i.e. the progressive loss of protective antibodies after recovery). In the present paper, we expand the analysis of this age-structured model and focus on the derivation of entomological and epidemiological results commonly used in the literature, following the works of Smith and McKenzie. We generalize their results to the age-structured case. In order to quantify the impact of neglecting structuring variables such as chronological age, we assigned values from the literature to our model parameters. While some parameters values are readily accessible from the literature, at least those about the human population, the parameters concerning mosquitoes are less commonly documented and the values of a number of them (e.g. mosquito survival in the presence or in absence of infection) can be discussed extensively. Our analysis, informed by parameter values from the literature, demonstrates that overlooking those structural variables of human and mosquito populations may result in inaccurate epidemiological predictions and suboptimal control strategies. We highlight the epidemiological implications of these findings and emphasize the necessity of considering age structure in future malaria control programs. •Analysis of an age-structured model for malaria transmission modeling.•Generalization of entomological and epidemiological formulas to the age-structured case.•Emphasize the importance of both chronological and infection ages on malaria transmission.•State of the art of the parameters then discussion about mosquitoes parameters.