Rift Valley fever in northern Senegal: A modelling approach to analyse the processes underlying virus circulation recurrence.

Rift Valley fever (RVF) is endemic in northern Senegal, a Sahelian area characterized by a temporary pond network that drive both RVF mosquito population dynamics and nomadic herd movements. To investigate the mechanisms that explain RVF recurrent circulation, we modelled a realistic epidemiological system at the pond level integrating vector population dynamics, resident and nomadic ruminant herd population dynamics, and nomadic herd movements recorded in Younoufere area. To calibrate the model, serological surveys were performed in 2015-2016 on both resident and nomadic domestic herds in the same area. Mosquito population dynamics were obtained from a published model trained in the same region. Model comparison techniques were used to compare five different scenarios of virus introduction by nomadic herds associated or not with vertical transmission in Aedes vexans. Our serological results confirmed a long lasting RVF endemicity in resident herds (IgG seroprevalence rate of 15.3%, n = 222), and provided the first estimation of RVF IgG seroprevalence in nomadic herds in West Africa (12.4%, n = 660). Multivariate analysis of serological data suggested an amplification of the transmission cycle during the rainy season with a peak of circulation at the end of that season. The best scenario of virus introduction combined yearly introductions of RVFV from 2008 to 2015 (the study period) by nomadic herds, with a proportion of viraemic individuals predicted to be larger in animals arriving during the 2nd half of the rainy season (3.4%). This result is coherent with the IgM prevalence rate (4%) found in nomadic herds sampled during the 2nd half of the rainy season. Although the existence of a vertical transmission mechanism in Aedes cannot be ruled out, our model demonstrates that nomadic movements are sufficient to account for this endemic circulation in northern Senegal.

Comparative Study of Intake, Apparent Digestibility and Energy and Nitrogen Uses in Sahelian and Majorera Dairy Goats Fed Hay of Vigna unguiculata.

This study aimed to compare digestive and metabolic characteristics in Sahelian (S) and Majorera (M) goat breeds. Six lactating females from each breed, with an average weight 27.0 ± 1.93 and 23.7 ± 1.27 kg, respectively, were used. Cowpea hay, variety 58/74, was offered as sole feed ingredient, at a rate of 2 kg of fresh matter per animal per day. The animals were placed in metabolic cages and a digestibility test was conducted according to an adaptation period of 15 days and a collection period of 7 days. The daily chemical components offered and refused and recovered faeces, urine and milk were measured in order to assess energy and nitrogen utilization. The M and S goats had similar levels of dry matter (DM) intake as well as nutrient digestibility. On a metabolic weight basis, dry matter intake, gross energy intake, metabolizable and energy intake, digestible energy and energy lost as methane production were significantly higher (p < 0.01) in M than in S goats. Urinary energy excretion was similar (p = 0.9) between breeds, while faecal energy output was higher in M than in S goats. The milk energy output from the M goats was higher than that the S goats (p < 0.05). However, metabolizable to net energy conversion efficiency (klm) was not affected by breed (p = 0.37), while N intake, milk N yield and faecal N losses, relative to metabolic weight, were significantly higher (p < 0.05) in M than in S goats. Similarly, the percentage of dietary N intake excreted in urine (UNIN) was higher in S than in M breeds. The breed factor had no effect on N retained, N digestibility, urinary N and N use efficiency. In conclusion, the M and S goats were similar in terms of energy and nitrogen use efficiency, despite higher daily milk production and DM consumption in the M goat. This suggests that the M breed is possibly more dependent on a dense nutrition diet than the S breed but requires less maintenance nitrogen.

Application of exponential random graph models to determine nomadic herders' movements in Senegal.

Understanding human and animal mobility patterns is a key to predict local and global disease spread. We analysed the nomad herds' movement network in a pilot area of northern Senegal and used exponential random graph models (ERGM) to investigate the reasons behind these movements. We interviewed 132 nomadic herders to collect information about nomad herd structures, movements, and reasons for taking specific routes or gathering in certain areas. We constructed a spatially explicit network with villages as the nodes and nomad herds' movements as the connecting edges. The final ERGM showed that node and edge attributes such as presence of cattle in the herd (odds ratio = 12, CI: 5.3, 27.3), morbidity (odds ratio = 3.6, CI: 2.3, 5.7), and lack of water (odds ratio = 2, CI: 1.3, 3.1) were important predictors of nomad herds' movements. This study not only provides valuable information for monitoring important livestock diseases such as Rift Valley Fever in Senegal, but also helps implement outreach, education, and intervention programs for other emerging and endemic diseases affecting nomadic herds.