Biology subjects

Sulaimon, T. A.

Publications and source records attributed to Sulaimon, T. A..

3 recordsLinked to original sources

bioRxiv2024

Modelling resource-driven movements of livestock herds to predict the impact of climate change on network dynamics

In East Africa, climate change is likely to profoundly impact livestock management and the potential spread of infectious diseases. Here, we developed a network model to describe livestock movements to grazing and watering sites, fitted it to data from the Serengeti district of Tanzania, and used it to explore how projected changes in resource availability due to climate change could impact future network structures and therefore infectious disease risks, using 2050 and 2080 as exemplar scenarios. Our modelled networks show increased connections between villages in grazing and watering networks, with connectivity increasing further in the future in correspondence with changes in vegetation and water availability. Our analyses show that targeted interventions to efficiently control regional disease spread may become more difficult, as village connectivity increases and disease vulnerability becomes more evenly distributed. This analysis also provides proof of principle for a novel approach applicable to agropastoral settings across many developing countries, where livestock trade plays a crucial role in maintaining local livelihoods but also in spreading disease.

ecology↗

bioRxiv2024

The potential impacts of vector host species fidelity on zoonotic arbovirus transmission

The interaction between vector host preference and host availability on vector blood feeding behaviour has important implications for the transmission of vector-borne pathogens. In particular in multi-host disease systems the fidelity of the vector biting behaviour has the potential to have important implications to disease outcomes, particularly when there are amplifying and dead-end hosts. Using a mathematical model we showed that vector fidelity to the host species they take a first blood meal from leads to non-homogeneous mixing between hosts and vectors. Taking Japanese encephalitis virus (JEV) as a case study, we investigated how vector preference for amplifying vs dead-end hosts and fidelity can influence JEV transmission. We show that in regions where pigs (amplifying hosts) are scarce compared to cattle (dead-end hosts preferred by common JEV vectors), JEV can still be maintained through vector fidelity. Our findings demonstrate the importance of considering fidelity as a potential driver of transmission, particularly in scenarios such as Bangladesh and India where the composition of the host community might initially suggest that transmission is not possible.

ecology↗

bioRxiv2022

Modelling the effectiveness of targeting Rift Valley fever virus vaccination using imperfect network information

Livestock movements contribute to the spread of several infectious diseases. Data on livestock movements can therefore be harnessed to guide policy on targeted interventions for controlling infectious livestock diseases, including Rift Valley fever (RVF) -- a vaccine-preventable arboviral fever. While detailed livestock movement data are available in many countries, such data are generally lacking in others, including many in East Africa, where multiple RVF outbreaks have been reported in recent years. Available movement data are imperfect, and the impact of imperfect movement data on targeted vaccination is not fully understood. Here, we used a network simulation model to describe the spread of RVF within and between 398 wards in northern Tanzania connected by cattle movements, on which we evaluated the impact of targeting vaccination using imperfect movement data. We show that pre-emptive vaccination guided by only market movement permit data could prevent large outbreaks. Targeted control (either by the risk of RVF introduction or onward transmission) at any level of imperfect movement information is preferred over random vaccination, and any improvement in information reliability is advantageous to their effectiveness. Our modelling approach demonstrates how targeted interventions can be carefully applied to inform animal and public health policies on disease control planning in settings where detailed data on livestock movements are unavailable or imperfect due to a lack of data-gathering resources.

genetics↗