Samuel Fuhrimann: Rift Valley Fever in Kenya: Analyses of prevention and control options from a multisector perspective

PhD-Project, University of Basel

The two recent Rift Valley Fever (RVF) epidemics in Kenya /1997/1998 and 2006/2007) resulted in severe socioeconomic consequences for the country. RVF is a viral zoonosis and a mosquito-borne disease that affects people, livestock and wildlife and thus is dealt with by multiple sectors. We address the need for closer cooperation between the two sectors to allocate limited resources more appropriately and to facilitate planning of concerted activities.

Methods

i) Mapping of stakeholders and institutional analysis; ii) Simulation of different options (combinations of vaccination, sanitary measures, surveillance, vector control and awareness campaigns) with an individual-based livestock demographic model; iii) Economic modeling to estimate costs of control per DALY averted and costs and benefits to the livestock sector and national economy.

Results

Up to 28 different agencies are relevant and need to be considered in collaborations on RVF (and zoonoses in general) prevention and control. The stakeholders go beyond the line animal and public health sectors, indeed, the most important actor is not within the health sectors.
The baseline and RVF-attributable mortalities can be simulated and show the losses due to RVF. We can retrieve proportions of livestock species (age/sex-stratified) and th number of infected slaughtered and sold animals that represent the highest risk of human infections. Small ruminants are most likely to spread the disease through livestock trade. Slaughtered infected sheep are an important risk factor to human RVF infection.
The last outbreak, only considering the official records, summed up to 4036 DALYs (or 340 / 100’000 corresponding to a fifth of TB DALYs in the same year).
A first cost-benefit analysis based on two consecutive animal RVF vaccinations one year prior to an outbreak was highly beneficial in terms of return to investment of the government.

Conclusions

The ratio of susceptible/immune hosts from the model supports the estimation of immunity levels years after a previous outbreak. It also considers normal and drought period, which is more realistic for Sahelian pastoral livestock production systems and is currently fitted to agro-pastoral and smallholder livestock systems. Our results help to consider best governmental investments regarding the reduction of economic losses and human morbidity/mortality, which, in return, improves future intersectoral contingency planning. A narrow scope of traditional One Health actors (health, livestock and environmental sectors) would weaken the control of zoonoses.