Figures and data in Rift Valley fever virus dynamics in a transhumant cattle system in The Gambia

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Tables
Additional files

8 figures, 4 tables and 1 additional file

Figures

Figure 1 with 3 supplements

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Distribution of (A) degree, (B) normalised betweenness, and (C) eigenvector centrality values based on cross-sectional household survey data on livestock movement.

Only a few households showed high centrality values, highlighting their importance in the network.

Figure 1—figure supplement 1

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A topological network depicting the overall connectivity among study households based on shared resource areas in The Gambia.

The network is undirected and unweighted, with grey edges. Coloured circles denote individual households within specific villages, with varying hues representing different study villages. White circles indicate shared water and grazing locations used by households. Squares represent transhumant household herds, which seasonally migrate over long distances (up to 80 km), establishing connections with household herds across villages. The transhumant movements are directed towards the Gambia river valley from within the Sahelian eco-region.

Figure 1—figure supplement 2

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Spearman’s rank correlation analysis illustrating the relationship between household (HH) Rift Valley fever virus (RVFV) seropositivity in cattle and unweighted, normalized (A) degree, (B) betweenness, and (C) eigenvector centrality (computed only on the giant component) values derived from this study.

Figure 1—figure supplement 3

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Spearman’s rank correlation analysis illustrating the relationship between the geographic distance separating connected households (HH) and their mean Rift Valley fever virus (RVFV) seropositivity of cattle in this study.

Figure 2

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Time series of the proportion of infectious cattle in the three subpopulations across the two eco-regions.

(A) The simulated Rift Valley fever (RVF) infection dynamics from the deterministic model (solid lines) together with 20 realisations of the stochastic model (dashed lines). (B) A magnified view highlighting the seasonal dynamics of Rift Valley fever virus (RVFV) transmission focused on the last 2 years of the 20-year deterministic simulation in the cattle subpopulations, highlighting finer seasonal variations (wet season = beige; dry season = cyan). The proportion of infectious cattle peaked at the latter part of the wet season, but infections quickly disappeared in the dry season in the Sahelian eco-region. Once transhumant herds begin to arrive in the Gambia river region, infections are predicted to rise. I=infectious cattle in each subpopulation. A square root transformation was applied to the y-axis for visualisation purposes using coord_trans(y = ‘sqrt’), while the data remained in its original scale.

Figure 3 with 1 supplement

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Extinction rate of Rift Valley fever virus (RVFV) over time (red line with 95% CI – grey ribbon), in the transhumant subpopulation (A) and the entire cattle population within the system (B) based on 1000 stochastic realisations, illustrating differences in the timing of local and system-wide extinctions, respectively.

Most of the local extinction occurred shortly after RVFV introduction into a fully susceptible population in the T subpopulation. Note: the timing of the local extinction in the T subpopulation depicted here represents the first extinction event within this subpopulation; re-infection occurs when the subpopulation returned to the river.

Figure 3—figure supplement 1

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Distribution of the number of local extinction events in the T subpopulation over an average transmission period of 13.7 years, based on stochastic simulations.

The x-axis shows the number of extinction events per simulation, and the y-axis shows the count of simulations exhibiting each number of extinctions.

Figure 4

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The full 10-year simulation of the weekly $R_{s t}$ (green) and force of infection ${(λ}_{i, s e a s o n})$ in each eco-region (blue = Sahelian, red = Gambia river eco-region).

Shaded areas correspond to the seasons (wet season = beige; dry season = cyan) in the last 2 years of the simulation. A square root transformation was applied to the y-axis for visualisation purposes using coord_trans(y = ‘sqrt’), while the data remained in its original scale.

Figure 5

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Predicted Rift Valley fever virus (RVFV) seroprevalence in each population subject to force of infection (FOI) during the wet and dry seasons.

(A) Cumulative growth of RVFV immunity over a 10-year period, representing the hypothetical lifespan of cattle, with no consideration for decay of RVFV seropositivity $(π = 0)$ . (B) Proportion of immune cattle after introducing a seropositivity decay parameter $(π = 0.00217)$ , aligning the predicted seroprevalence with observed data. Observed seroprevalence across different age classes in the three structured cattle populations in The Gambia is shown as dots, with 95% confidence intervals (CI) as error bars. P: cattle exposed to RVFV infection and recovered, assumed to be seropositive.

Figure 6

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The general linear model (GLM) (solid line) and Loess (dotted line) smoothing plots of the relationship between percentage change in predicted seroprevalence of each structured subpopulation (M, L, and T) and percentage change in parameter values constrained within ±20% of the mean posterior value.

Figure 7

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Map of study location – The Gambia.

(A) Illustrates the location of villages selected for household survey and ruminant sampling. Map created in QGIS 3.28.3; land cover data derived from Global Land Cover 2000 (GLC2000) Project. (B) Spatial range of transhumant cattle movements in The Gambia identified from the household survey. Movements originated from study villages (represented as red squares) and extended to destination villages, which are either other study villages or villages not selected for this study (represented as black triangles). This study was conducted during the dry season, and all transhumant herds were sampled at their destination villages. Distinct directional movements between homestead villages and their respective destinations are illustrated with blue arrows. The Gambia river is depicted as the meandering white line running the length of the country. The map was generated using the igraph package in R.

Figure 8

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Epidemiological model of Rift Valley fever virus (RVFV) transmission and infection dynamics among the cattle subpopulations in The Gambia.

(A) Schematic representation of ecoclimatic region and seasonal combinations that influence RVFV transmission between the Sahelian areas and the Gambia river eco-region. (B) The transmission matrices that determined possible RVFV transmissions between the subpopulations during each season. (C) Transmission framework of the within eco-region RVFV transmission; parameters are defined within the main text.

Tables

Table 1

Mean posterior values and 95% credible intervals (CrI) of the estimated parameters.

Parameter description	Notation	Unit	Mean value	95% CrI
Per capita birth rate	$b$	day^–1	0.0022	0.0012–0.0033
Per capita natural death rate	μ	day^–1	0.0017	0.0010–0.0023
RVF specific mortality rate	$γ$	day^–1	0.0758	0.0358–0.1868
RVF recovery rate	$δ$	day^–1	0.1161	0.0500–0.1917
Scaling factor	$ψ$	–	2.0508	0.9224–3.1282
Wet season transmission parameter in the Sahelian eco-region	$β_{s, w e t}$	*	1.4×10^–6	6.0×10^–7 – 2.2×10^–6
Wet season transmission parameter in the Gambia river eco-region	$β_{r, w e t}$	*	3.7×10^–6	1.9×10^–6 – 5.3×10^–6
Dry season transmission parameter in the Gambia river eco-region	$β_{r, d r y}$	*	3.1×10^–6	1.7×10^–6 – 4.4×10^–6

*

(Infected·susceptible·day)⁻¹.

Table 2

Summary of estimated seasonal reproduction number $(R_{s t})$ and regio-specific force of infection $λ_{i}$ .

Seasons	Mean $R_{s t}$	Maximum $R_{s t}$	Minimum $R_{s t}$	Avg. weeks $R_{s t} > 1$
Wet	1.15	1.40	0.91	9/17
Dry	1.02	1.11	0.87	23/35
Seasons	Region	Mean $λ_{i}$	Maximum $λ_{i}$	Minimum $λ_{i}$
Wet	Sahelian	0.008	0.05	0.0001
	river	0.003	0.005	0.0002
Dry	Sahelian	–	–	–
	river	0.002	0.018	0.0001

Table 3

The elasticity for all eight parameters in the general linear model (GLM).

The parameters with the largest coefficient are shown in bold.

	Subpopulation M		Subpopulation L		Subpopulation T
Parameter	Intercept	Coefficient	Intercept	Coefficient	Intercept	Coefficient
$β_{s, w e t}$	–0.004	0.140	–0.005	–0.027	0.008	–0.032
$β_{r, w e t}$	–0.014	0.018	0.064	–1.023	0.059	–1.485
$β_{r, d r y}$	–0.028	0.180	0.074	1.010	0.056	1.604
μ	–0.104	–3.965	0.151	–4.731	0.091	–4.251
$b$	–0.154	3.603	0.108	4.784	0.059	4.230
$γ$	–0.001	–1.016	0.055	–1.735	0.057	–1.875
$δ$	–0.019	0.874	0.059	1.500	0.073	1.571
$τ$	–0.004	0.140	–0.005	–0.027	0.008	–0.032

Table 4

Preliminary parameter values for the susceptible-infectious-recovered (SIR) model.

Parameter description	Notation	Value	Unit	Reference
Per capita birth rate	$b$	0.00215	day^–1	Gachohi et al., 2016
Per capita natural death rate	μ	0.0016	day^–1	Nicolas et al., 2014
RVF specific mortality rate	$γ$	0.075	day^–1	Gachohi et al., 2016
RVF recovery rate	$δ$	1/8	day^–1	Durand et al., 2020
Scaling factor	$ψ$	2	–	Assumed
Decay rate of RVFV seropositivity	$π$	0.005	week^–1	Assumed
Total M population	$N_{M}$	177,004		2016 Livestock Census
Total L population	$N_{L}$	80,433		2016 Livestock Census
Total T population	$N_{T}$	35,400		2016 Livestock Census

Additional files

MDAR checklist: https://cdn.elifesciences.org/articles/107346/elife-107346-mdarchecklist1-v1.docx
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Essa Jarra
Divine Ekwem
Sarah Cleaveland
Daniel T Haydon

(2026)

Rift Valley fever virus dynamics in a transhumant cattle system in The Gambia

eLife 14:RP107346.

https://doi.org/10.7554/eLife.107346.3

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Distribution of (A) degree, (B) normalised betweenness, and (C) eigenvector centrality values based on cross-sectional household survey data on livestock movement.

A topological network depicting the overall connectivity among study households based on shared resource areas in The Gambia.

Spearman’s rank correlation analysis illustrating the relationship between the geographic distance separating connected households (HH) and their mean Rift Valley fever virus (RVFV) seropositivity of cattle in this study.

Time series of the proportion of infectious cattle in the three subpopulations across the two eco-regions.

Distribution of the number of local extinction events in the T subpopulation over an average transmission period of 13.7 years, based on stochastic simulations.

The full 10-year simulation of the weekly Rst (green) and force of infection (λi,season) in each eco-region (blue = Sahelian, red = Gambia river eco-region).

Predicted Rift Valley fever virus (RVFV) seroprevalence in each population subject to force of infection (FOI) during the wet and dry seasons.

Map of study location – The Gambia.

Epidemiological model of Rift Valley fever virus (RVFV) transmission and infection dynamics among the cattle subpopulations in The Gambia.

Mean posterior values and 95% credible intervals (CrI) of the estimated parameters.

Summary of estimated seasonal reproduction number (Rst) and regio-specific force of infection λi.

The elasticity for all eight parameters in the general linear model (GLM).

Preliminary parameter values for the susceptible-infectious-recovered (SIR) model.

MDAR checklist

Downloads (link to download the article as PDF)

Open citations (links to open the citations from this article in various online reference manager services)

Cite this article (links to download the citations from this article in formats compatible with various reference manager tools)

The full 10-year simulation of the weekly $R_{s t}$ (green) and force of infection ${(λ}_{i, s e a s o n})$ in each eco-region (blue = Sahelian, red = Gambia river eco-region).

Summary of estimated seasonal reproduction number $(R_{s t})$ and regio-specific force of infection $λ_{i}$ .