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Transmission potential of Rift Valley fever virus over the course of the 2010 epidemic in South Africa.

Métras R, Baguelin M, Edmunds WJ, Thompson PN, Kemp A, Pfeiffer DU, Collins LM, White RG - Emerging Infect. Dis. (2013)

Bottom Line: A Rift Valley fever (RVF) epidemic affecting animals on domestic livestock farms was reported in South Africa during January-August 2010.The epidemic fade-out likely resulted first from the immunization of animals following natural infection or vaccination.Increased availability of vaccine use data would enable evaluation of the effect of RVF vaccination campaigns.

View Article: PubMed Central - PubMed

Affiliation: Royal Veterinary College, Hatfield, UK.

ABSTRACT
A Rift Valley fever (RVF) epidemic affecting animals on domestic livestock farms was reported in South Africa during January-August 2010. The first cases occurred after heavy rainfall, and the virus subsequently spread countrywide. To determine the possible effect of environmental conditions and vaccination on RVF virus transmissibility, we estimated the effective reproduction number (Re) for the virus over the course of the epidemic by extending the Wallinga and Teunis algorithm with spatial information. Re reached its highest value in mid-February and fell below unity around mid-March, when vaccination coverage was 7.5%-45.7% and vector-suitable environmental conditions were maintained. The epidemic fade-out likely resulted first from the immunization of animals following natural infection or vaccination. The decline in vector-suitable environmental conditions from April onwards and further vaccination helped maintain Re below unity. Increased availability of vaccine use data would enable evaluation of the effect of RVF vaccination campaigns.

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Related in: MedlinePlus

Distribution of D0 by time and distance [D0(s,t)]. D0(s,t) is a measure of spatiotemporal interaction between cases that was estimated by using the space–time K-function (19,20); the distribution is indicated by the pink dashed line. The green, yellow, and blue lines are the smoothed distributions, which were obtained with bandwidth values of 1, 3, and 5, respectively. A) Plot of D0(s,t) values by distance on day 1. B) D0(s,t) values by time at distance of 5 km. C) Plot of D0(s,t) values by distance on day 5. D) D0(s,t) values by time at distance of 15 km.
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Figure 3: Distribution of D0 by time and distance [D0(s,t)]. D0(s,t) is a measure of spatiotemporal interaction between cases that was estimated by using the space–time K-function (19,20); the distribution is indicated by the pink dashed line. The green, yellow, and blue lines are the smoothed distributions, which were obtained with bandwidth values of 1, 3, and 5, respectively. A) Plot of D0(s,t) values by distance on day 1. B) D0(s,t) values by time at distance of 5 km. C) Plot of D0(s,t) values by distance on day 5. D) D0(s,t) values by time at distance of 15 km.

Mentions: The shape of the D0(s,t) plot, peaking for short space–time windows (Figure 3), suggested that most of the transmission was attributed to short-distance mechanisms (e.g., local vector dispersal) rather than long-distance mechanisms (e.g., movement of infectious animals or wind carriage of vectors) (19). By using this generation interval for the duration of the epidemic, a constant and high importance of short-distance transmission mechanisms was assumed. However, as the epidemic grew, these short-distance transmission mechanisms were likely to be less important; or in, other words, as farms around a case became infected and immune, short-distance transmission was likely to be less involved in disease spread. Thus, we investigated the variations of Re by giving less weight to short-distance transmission and more weight to long-distance transmission. To obtain such serial interval distributions, the D0(s,t) distribution was flattened by using a 2-dimensional double exponential kernel function with bandwidth values equal to 1, 3, and 5, resulting in 3 smoothed surfaces (Figure 3). It was assumed that the bandwidth equal to 1 would better correspond to the serial interval distribution at the early stage of the epidemic and that bandwidth values 3 and 5 would better describe the intensity of the transmission when the population started to be immune (i.e., at the later stages of the epidemic).


Transmission potential of Rift Valley fever virus over the course of the 2010 epidemic in South Africa.

Métras R, Baguelin M, Edmunds WJ, Thompson PN, Kemp A, Pfeiffer DU, Collins LM, White RG - Emerging Infect. Dis. (2013)

Distribution of D0 by time and distance [D0(s,t)]. D0(s,t) is a measure of spatiotemporal interaction between cases that was estimated by using the space–time K-function (19,20); the distribution is indicated by the pink dashed line. The green, yellow, and blue lines are the smoothed distributions, which were obtained with bandwidth values of 1, 3, and 5, respectively. A) Plot of D0(s,t) values by distance on day 1. B) D0(s,t) values by time at distance of 5 km. C) Plot of D0(s,t) values by distance on day 5. D) D0(s,t) values by time at distance of 15 km.
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Related In: Results  -  Collection

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Figure 3: Distribution of D0 by time and distance [D0(s,t)]. D0(s,t) is a measure of spatiotemporal interaction between cases that was estimated by using the space–time K-function (19,20); the distribution is indicated by the pink dashed line. The green, yellow, and blue lines are the smoothed distributions, which were obtained with bandwidth values of 1, 3, and 5, respectively. A) Plot of D0(s,t) values by distance on day 1. B) D0(s,t) values by time at distance of 5 km. C) Plot of D0(s,t) values by distance on day 5. D) D0(s,t) values by time at distance of 15 km.
Mentions: The shape of the D0(s,t) plot, peaking for short space–time windows (Figure 3), suggested that most of the transmission was attributed to short-distance mechanisms (e.g., local vector dispersal) rather than long-distance mechanisms (e.g., movement of infectious animals or wind carriage of vectors) (19). By using this generation interval for the duration of the epidemic, a constant and high importance of short-distance transmission mechanisms was assumed. However, as the epidemic grew, these short-distance transmission mechanisms were likely to be less important; or in, other words, as farms around a case became infected and immune, short-distance transmission was likely to be less involved in disease spread. Thus, we investigated the variations of Re by giving less weight to short-distance transmission and more weight to long-distance transmission. To obtain such serial interval distributions, the D0(s,t) distribution was flattened by using a 2-dimensional double exponential kernel function with bandwidth values equal to 1, 3, and 5, resulting in 3 smoothed surfaces (Figure 3). It was assumed that the bandwidth equal to 1 would better correspond to the serial interval distribution at the early stage of the epidemic and that bandwidth values 3 and 5 would better describe the intensity of the transmission when the population started to be immune (i.e., at the later stages of the epidemic).

Bottom Line: A Rift Valley fever (RVF) epidemic affecting animals on domestic livestock farms was reported in South Africa during January-August 2010.The epidemic fade-out likely resulted first from the immunization of animals following natural infection or vaccination.Increased availability of vaccine use data would enable evaluation of the effect of RVF vaccination campaigns.

View Article: PubMed Central - PubMed

Affiliation: Royal Veterinary College, Hatfield, UK.

ABSTRACT
A Rift Valley fever (RVF) epidemic affecting animals on domestic livestock farms was reported in South Africa during January-August 2010. The first cases occurred after heavy rainfall, and the virus subsequently spread countrywide. To determine the possible effect of environmental conditions and vaccination on RVF virus transmissibility, we estimated the effective reproduction number (Re) for the virus over the course of the epidemic by extending the Wallinga and Teunis algorithm with spatial information. Re reached its highest value in mid-February and fell below unity around mid-March, when vaccination coverage was 7.5%-45.7% and vector-suitable environmental conditions were maintained. The epidemic fade-out likely resulted first from the immunization of animals following natural infection or vaccination. The decline in vector-suitable environmental conditions from April onwards and further vaccination helped maintain Re below unity. Increased availability of vaccine use data would enable evaluation of the effect of RVF vaccination campaigns.

Show MeSH
Related in: MedlinePlus