Presented at Speke Resort ,Munyonyo, Kampala, Monday 16th November 2015

†

Montgomery , 1912, Daubney 1931, Davies 1975, Jost et al., 2010, Nanyingi et al., 2015

RVF is a viral zoonosis that occurs

in a (5-10yrs) cycle, it was 1st

described in Kenya(1912) & isolated

in 1931.

Caused by a Phlebovirus in

Bunyaviridae(Family), transmitted by

mosquitoes: Aedes, culicine spp.

RVFV is high impact

transboundary pathogen (OIE) and

category A select agent(CDC ).

The RVFV genome has tripartite

RNA segments : large (L), medium

(M), and small (S) contained in a

spherical (80–120 nm in diameter)

lipid bilayer.

Major epidemics have occurred

throughout Africa, Arabian Peninsula

3

Precipitation: ENSO/Elnino above

average rainfall leading flooding

( dambos”).

Hydrological drivers of vector emergency:

(IEP transovarial maintenance by aedes 1º

and culicine 2º mosquitoes.( vectorial

capacity/ competency)

Dense green vegetation cover = Persistent

NDVI.(0.1 units > 3 months)

Soil types: Solonetz, Solanchaks,

planosols (drainage/moisture).

Elevation : altitude <1,100m asl (flooding)

Linthicum et al., 1999; Anyamba et al., 2009; Hightower et al., 2012

r

h

Culex

eggs

Aedes

eggs

t0 Jan Dec

t20

h

Aedes

eggs r

Culex

eggs

t0

Jan Dec

Adult

Den

sity

A

dult

Den

sity

Humans Mild : IP(4-6 days)

Flu-like fever, myaglia,

joint pains, headache,

Neck stiffness,

photosensitivity,

inappetance & vomiting

Severe:

Ocular form(Retinal)

blurred /Loss of vision

Meningoencephalitis

Memory loss,

Hallucinations,

Vertigo, convulsions,

lethargy and coma.

Neurological deficit

Haemorrhagic icterus

Jaundice, hematemesis

Hematochezia,

Ecchymoses. CFR≥50%

OCFR≤1%

Animals : Cattle, sheep,camels

Goats & Buffaloes

Hyperacute form

Sporadic abortions

indicative of epidemic

Pyrexia (40-42 C)

Sudden death.

Acute form

Death (24-48hrs)

Jaundice

Mortality rates up 60%

Subacute and

inapparent forms

Detectable by serology

Burden to older animals

Decreased production

1997/98 & 2006/7 EA outbreaks

led to livestock mortality, trade

losses $500 Million

.

Estimated 158 human deaths, 3.4

DALYs per 1000 people.

Trade disruptions and High

intervention costs (vaccinations)

WHO, FAO factsheets, Bird et al., 2009

Hypothesis:

There is persistent RVF virus circulation in disease endemic

areas of Northern Kenya and epidemics have potential

associations with environmental and climatic parameters

Objective:

To detect circulation of RVF virus in ruminants in Garissa

County, Kenya during an inter-epidemic period (IEP).

Bird et al., 2009

Garissa County a semi-arid zone in North eastern

part of Kenya, bordering Somalia to the East.

Located between latitude 0° 58’ N and 1° 30’ S and

longitudes 38° 34’ E and 41°05’ W

It covers approximately 33,620 km2, with a

population of 623,060 persons and 1.5 million

livestock.

Garissa County has low altitude ranging from 70-

400 m above sea level.(Flood plain)

It experiences long rains (MAM) and short rains

(OND) with annual averages of 300-600 mm and

diurnal temperature ranges of 20-38°C.

Sampling: Danyere, Kone and Sankuri, Korakora,

Bouralgi, Disso and Yumbis and Hulugho divisions.

A cross-sectional study conducted in March 2013 and July 2014 .

A multistage sampling : Two stage cluster sampling technique, with

divisions selected a priori , the herd was used as PSU.

415 animals were sampled from the identified herds by jugular

venipuncture into vacutainer tubes.

370 Serum samples collected from sheep, goats and cattle were

analyzed for total antiRVFV (IgG) antibodies using a competetive indirect

competitive ELISA (cELISA)-ID Vet®.

Absorbance (Optical density-OD) was measured at 450 nm using a

microplate reader, Gen5 v1.05 software (BioTek) was used for data

analysis.

Serological positivity was detectable as suspect or negative (S/N %)

value of ≤ 40%[21]. Samples with S/N ≥ 40 - ≤ 50%

Descriptive analyis was done for host demographic characteristics:

Host risk factors for RVFV seropositivity were examined by univariable

analysis. Unadjusted odds ratios (OR) for seropositivity were estimated

using log linear regression model.

A mixed effects logistic regression model MELM (glmer) was used to

determine the association of (Age, Sex, Species) on RVF

seroconversion with location as the random effect.

Using ArcGIS 10.2.2 (ESRI, 2014), GPS data were imported in

ArcMap. hydrological layers were overlaid on the county and

hydrological profile.

All statistical analyses was performed using R version 3.1.3 software.

Study location Species Number sampled Age

Male Female ≤12months >12months

Bouralgi Cattle 0 0 0 0

Goats 0 14 2 12

Sheep 2 9 3 8

Danyere Cattle 0 0 0 0

Goats 1 27 0 28

Sheep 2 14 0 16

Disso Cattle 0 0 0 0

Goats 2 17 10 9

Sheep 1 15 4 12

Hulugho Cattle 0 0 0 0

Goats 1 12 0 13

Sheep 3 13 3 13

Kone Goats 9 100 25 84

Sheep 3 12 1 14

Korakora Cattle 2 10 6 6

Goats 0 19 0 19

Sheep 1 5 0 6

Sankuri Goats 12 26 11 27

Sheep 0 0 0 0

Yumbis Goats 3 28 7 24

Sheep 2 5 0 7

Total 44 326 72 298

Seropositivity was

evenly distributed.

Visual

examination

suggests high

correlation of

seropositivity with

waterbodies,

forests.

Spatial

dependency was

not tested.

R-INLA for

spatiotemporal

analysis??

Goats Sheep Cattle

Location N SP (%) 95% C.I N SP (%) 95% C.I N SP (%) 95% C.I

Bouralgi 14 50 23.8-76.2 11 45.5 16-74.9 _ _ _

Danyere 28 35.7 18-53.5 16 37.5 13.8-61.2 _ _ _

Disso 19 5.3 4.3-15.3 16 12.5 3.7-28.7 _ _ _

Hulugho 13 76.9 54-99.8 16 31.2 8.5-54 _ _ _

Kone 109 16.5 9.5-23.5 15 40 15.2-64.8 _ _ _

Korakora 19 36.8 15.2-58.5 6 16.7 13.2-46.5 12 33.3 6.7- 60

Sankuri 38 21.1 8.1-34 _ _ _ _ _ _

Yumbis 31 29 13.1-45 7 42.9 6.2-79.5 _ _ _

The overall RVFV IgG antibody seroprevalence of the 370 analyzed

sera from all species in the 8 study locations was 27.6% (CI 23, 32.1).

The overall seropositivity for cattle, sheep and goats was 33.3%

(4/12), 32.2 % (28/87) and 25.8% (70/271) respectively.

Total

sampled

RFV

positive

Seroprevalence (%)

confidence interval (C.I)

Goats sex Female 243 64 26.3 (20.8-31.9)

Male 28 6 21.4 (6.2-36.6)

Age >12months 216 69 31.9 (25.7- 38.2)

≤12months 55 1 1.8 (-1.7-5.3)

Sheep sex Female 73 22 30.1(19.6-40.7)

Male 14 6 42.6 (16.9-68.8)

Age >12months 76 27 35.5 (24.8-46.3)

≤12months 11 1 9.1(-7.9-26.1)

The overall seroprevalence for all male species was 31.8% and

females 27%.

RVF Seroprevalence

Variable Levels OR 95%CI p value

Sex Female 1* - -

Male 1.17 0.55-2.48 0.65

Species Caprine 1* _ -

Bovine 1.07 0.55-15.87 0.19

Ovine 1.05 0.58-1.88 0.86

Age <12 1* - -

>12 18.91 5.51-120.17

< 0.0001†††

Seropositivity increased with advanced age, animals >12 months old

had an 18 fold likelihood to be seropositive than animals ≤12 months

OR= Odds Ratio, CI= Confidence Interval, *= Reference level, † = Significance level

The detection of RVFV IgG antibodies in ruminants from Garissa

County during inter-epidemic (IEP) period, corroborates earlier studies

reporting high seropositivity .

Increased likelihood for high RVF seropositivity with age has been

demonstrated in Mozambique, Madagascar and Tanzania in livestock

and humans, hence illustrating the one health dimension in disease

transmission.

Human longitudinal studies in Garissa have indicated presence of

RVFV that was likely be related to livestock migration via

transboundary trade from Somalia.

IgG antibodies suggest a previous exposure of animals to RVFV and

may indicate sub-clinical circulation.

High correlation of animal- human cases in Garissa. In 2006, 11

human deaths due to RVF was reported and in 2011 >1000 humans

had 15% seroprevalence for RVFV.

Lichoti et al., 2014 , Owange et al., 2015, Fafetine et al ., 2013, Heinrich et al., 2012

The lack of financial resources greatly influenced the sampling ability

to obtain the optimal effective sample size (ESS) of study animals.

There was skewed distribution in sampled species by age and sex,

difficulty in determining the exact age of animals and livestock density.

Logistic challenges led to our inability to restrain and hence sample

more cattle in other locations. therefore no remarkable statistical

inferences can be concluded on this species.

This is a one point estimate of disease in a highly mobile animal

population and may not account for host migration patterns and

prospective longitudinal cohort studies may be recommended.

The results presented here suggest long-term animal exposure to

RVFV in the area and confirm that high proportions of animals in

Garissa County are still at risk of RVF infection.

This is the first study to estimate ICC() for RVF in Garissa and forms

basis for estimating ESS in multistage cluster sampling for studies

investigating low contagious infectious vector-borne diseases

There is need for increased preparedness and response in RVF

endemic areas by conducting animal-human syndromic sero-

surveillance as part of one health early warning system.

Molecular and ecological investigations focusing on pathogen

discovery in vectors and soils should be fostered at a regional level as

part of one health EWS outbreak preparedness.

Anyamba et al. Prediction, assessment of the Rift Valley fever activity

in East and Southern Africa 2006-2008 and possible vector control

strategies. Am J Trop Med Hyg. 2010;83(2 Suppl):43-51.

Centers for Disease Control, Prevention. Rift Valley Fever--East

Africa, 1997-1998. MMWR Morb Mortal Wkly Rep. 1998;47(13):261-4.

Hightower et al. Relationship of climate, geography, and geology to

the incidence of Rift Valley fever in Kenya during the 2006-2007

outbreak. Am J Trop Med Hyg. 2012;86(2):373-80.

LaBeaud et al. Spectrum of Rift Valley fever virus transmission in

Kenya: insights from three distinct regions. Am J Trop Med Hyg

2007;76:795–800.

Nanyingi et al. A systematic review of Rift Valley Fever epidemiology

1931-2014. Infect Ecol Epidemiol. 2015;5:28024

WHO. Rift Valley Fever in Kenya, Somalia and the United Republic of

Tanzania 2007. http://www.who.int/csr/don/2007_05_09/en/

Study participants from Garissa County(animal owners)

Drs. Jackson Kinyua, Rashid Mohammed, Stephen Gathogo for

administrative, logistical support and expert guidance during field

sampling

Ngatia Mathenge and Nahashon Thuo for their assistance in animal

sampling and sample preparation.

DVS(CVL),KEMRI-CDC,USAMRU

Contact : mnanyingi@kemricdc.org, mnanyingi@gmail.com