Cross-cutting

FUTA cross-cutting model

Lead modeller: Ezra Gayawan

Institution(s): Federal University of Technology Akure (FUTA)

Brief description of model:

Our geospatial models characterise variations in the transmission of infectious diseases and other issues of public health importance across small geographical units. The focus is to estimate the geographical distribution of transmission dynamics and to quantify the impact of interventions across geographical units in order to aid the understanding of disease progression at different spatial units and allow for local-level planning. Through geostatistical models, we explore the impact of climate, environmental, or other relevant indicators on disease dynamics and vaccine coverage across geographical settings. In this project, firstly, we developed a Bayesian hierarchical model with latent Gaussian layers to quantify and assess the impact of varying levels of women’s empowerment on different vaccination coverage including BCG, DPT 1 to 3, MCV, and Zerodose in Nigeria while accounting for the effects of socioeconomic and demographic characteristics of children. Secondly, we considered a flexible bivariate copula model capable of jointly accounting for the association between two binary target variables. The model leverages the Gaussian Markov random field to quantify spatial interactions between administrative regions across fourteen contagious Western African countries. We used this model to study joint vaccine coverages, for instance, BCG and all basic vaccinations. This allows us to quantify, at spatial granularity, the chances of receiving all basic vaccinations given that the child received a BCG dose at birth across the African countries.

Key publication(s):

Gayawan, E., Egbon, O. A. and Adegboye, O. (2023) Copula based trivariate spatial modeling of childhood illnesses in Western African countries. Spatial and Spatio-temporal Epidemiology Vol. 46, 100591

Gayawan, E. and Egbon, O. A. (2023) Spatio-temporal mapping of stunting and wasting in Nigerian children: A bivariate mixture modeling Spatial Statistics Vol 58 100785

Gayawan, E., Egbon, O. A. and Adebayo, S. B. (2022) Spatial modelling of the joint burden of malaria and anaemia co-morbidity in children: A Bayesian geoadditive perspective. Communication in Statistics: Data Analysis, Case Studies and Applications Vol. 8(2) Pages Pages 264-281

Model code (where available):

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IP Tunis cross-cutting model

Lead modeller: Slimane Ben Miled

Link to all modelling group members

Institution(s): Institut Pasteur de Tunis

Brief description of model:

In low- and middle-income countries (LMICs), such as Tunisia and Niger, cervical cancer remains a pressing public health issue. The burden of HPV infection and associated cervical cancer is disproportionately higher in LMICs, where screening and vaccination rates are often lower than in high-income countries. Cultural and social factors, limited access to healthcare services, and low sexual health literacy contribute to this higher burden in LMICs. In Tunisia, cervical cancer ranks second among gynecological cancers of women, with an estimated 250 to 300 new cases per year. Despite the prevalence of HPV-related cervical infections, preventive strategies, including HPV vaccination, have not been established. The proposed project seeks to address these gaps by employing comparative mathematical models, considering demographics, culture, and healthcare factors, to identify economically efficient strategies for HPV prevention and assess the burden of associated cancers. This project aims to deliver a Cost effectiveness report to guide decision-making regarding the potential introduction of HPV vaccination into the national immunization program, considering budget impact analysis taking into account direct and indirect cost. Overcoming scientific and technical challenges, such as acquiring precise data on HPV prevalence and cultural factors influencing vaccine perceptions and acceptance, the project will provide invaluable insights into effective and cost-efficient HPV vaccination strategies, ultimately reducing the burden of HPV-related diseases in LMICs like Tunisia.

Figure 1: represent effect of male and female cross layer on cervical cancer (cross layer means marital male/female that have an extra-conjugal relationship)

Figure 2: the effect of maximal sexual frequency act by year at the sexual activity peak and at 50 yo on cervical cancer.

Key publication(s):

Model code (where available):

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