Brucellosis is a common bacterial zoonotic infection but data on the prevalence among humans and animals is limited in Kenya. A cross-sectional survey was conducted in three counties practicing different livestock production systems to simultaneously assess the seroprevalence of, and risk factors for brucellosis among humans and their livestock (cattle, sheep, camels, and goats). A two-stage cluster sampling method with random selection of sublocations and households was conducted. Blood samples were collected from humans and animals and tested for
Disclaimer: The findings and conclusions in this report are those of the authors and do not necessarily represent the official position of the Centers for Disease Control and Prevention.
Brucellosis, an infection caused by gram-negative bacteria of the genus
Human brucellosis is mainly transmitted from animal reservoirs through consumption of unpasteurized dairy products and undercooked meat products, inhalation of contaminated dust and contact with infected animal body fluids or tissues.
In animals, although specific
The control of brucellosis has been achieved in many developed countries. However, for other parts of the world including Latin America, the Middle East, Spain, parts of Africa, and western Asia brucellosis remains an endemic disease that causes more than 500,000 human infections each year.
Despite the public health importance of brucellosis, its incidence and prevalence in animals and humans, as well as its socioeconomic impact, remain poorly understood in Kenya. In addition, despite its zoonotic transmission, few studies have investigated the burden and risk factors for animal and human brucellosis simultaneously among people and livestock living together. Taking into consideration different animal production systems, our objective was to determine the seroprevalence of
We surveyed three administrative counties, each representing a different predominant livestock production system: Kiambu (small-holder system), Kajiado (agropastoral system) and Marsabit (pastoral system) ( Map of Kenya showing the three counties where the study was carried out. Each study county represents a predominantly unique production system; Kiambu (small-holder system), Kajiado (agropastoral system) and Marsabit (pastoral system).
We calculated the number of persons to be sampled based on an estimated seroprevalence of 50% for Kajiado and Marsabit and 5% for Kiambu, with an error margin of 5% and 2%, respectively, at the 95% confidence level.
For animals, we used a seroprevalence of 15% for Kajiado and Marsabit and 2% in Kiambu
We applied a two-stage random sampling method to identify study households in each county. In the first stage, sublocations were stratified by predominant production system and a 10% random sample was subsequently selected in each stratum. This resulted in 21, 13, and 10 sublocations sampled in Kiambu, Kajiado, and Marsabit counties, respectively. In the second stage, we first calculated the number of households to be sampled within each sublocation based on the total human population in the sublocation, then randomly generated geographical coordinates using ArcGIS to correspond to the number of households to be sampled. Coordinates were loaded into a global positioning system device to guide study teams in identifying households. Each study team comprised a nurse, two veterinarians/paravets, a laboratory technologist, one/two animal handlers, and a village guide. Within the prescribed geocode, households were randomly identified using the “spin the bottle” method.
A household was defined as a group of people who use a common cooking area. For each household, up to three persons aged 5 years and above were randomly selected and sampled. Sampling of the livestock was conducted per species (cattle, goat, sheep, and camels) in proportion to size of the herd. All animals in households with ≤ 15 animals were sampled while for farms with larger herd sizes, a maximum of 15 animals per species were sampled. Random animal selection was attempted in this case.
In Kiambu and Kajiado counties, blood samples were collected from eligible persons and from livestock between November and December 2012. Sampling in Marsabit took place in September 2013. Serum was separated from clotted blood by centrifugation at 3,000 ×
Structured questionnaires pre-loaded into smartphones were administered by the team nurse to collect both household-level and individual-level risk factors for brucellosis. The team interviewed heads of households on types of livestock kept, handling of livestock and their products, consumption of animal products, history of brucellosis in the household, level of education, socioeconomic status, demographic characteristics, and herd management.
Human samples were tested using the IBL-America IgG enzyme-linked immunosorbent assay (ELISA) kits (Minneapolis, MN), whereas animal samples were tested using Svanova Biotech AB (Uppsala, Sweden) ELISA kits, that is SVANOVIR®
Cattle sera were first incubated in
All analyses were done using STATA 12 (Stata Corporation, College Station, TX). Risk factor analysis was performed at the human, herd, and household levels, whereas univariate analysis was performed on human demographic factors (age, gender, education, and primary occupation). The animal-related human factors analyzed included livestock ownership, contact with or consumption of animals or their products, and development of disease symptoms within the last year. Factors characterizing animals or herds, such as breed, age, herd size, grazing system, and breeding system were also analyzed.
Multivariate logistic regression was used to identify factors associated with brucellosis seropositivity and to estimate the magnitude of the adjusted odds ratios (aORs) for each factor while controlling for other confounding factors. To account for clustering, the svyset command in Stata 12 was used to specify clustering at sublocation and household levels. All analyses were subsequently carried out while accounting for clustering by applying the prefix svy in Stata 12. Univariate analysis was conducted for explanatory variables (biologically plausibly associated with brucellosis seropositivity) and those with a
Ethical clearance and approval was obtained from the KEMRI Ethical Review Committee (ERC) and Animal Care and Use Committee (ACUC), and CDC Institutional review board. Other approvals were obtained from the Ministry of Health and the Ministry of Agriculture Livestock and Fisheries. Appropriate consenting processes were followed within households before sampling was initiated and data confidentiality was strictly maintained.
A total of 1,088 households were surveyed; 505 (46%), 306 (28%), and 277 (26%) from Kiambu, Kajiado, and Marsabit counties, respectively. The mean household size was four persons (mean range = 4.1–4.5) in the three counties. Among household heads (HHD), 72% were males and the mean age was 52.0 years (range = 18–94 years). Five percent of the household heads in Marsabit County had at least high school education compared with 46% and 56% in Kajiado and Kiambu, respectively. Seventy-seven percent of the households owned at least one livestock species (sheep, goat, cattle, and camels). Among the livestock owning households, 73% owned cattle, 56% owned goats, 45% owned sheep, and 12% owned camels.
A total of 2,811 persons, 1,255 (45%) from Kiambu, 791 (28%) from Kajiado and 765 (27%) from Marsabit, consented and were interviewed. Fifty-four percent of the persons interviewed were female. The mean age was 35.6 years (range = 5–96 years).
The highest household and herd prevalence was in Marsabit and the lowest in Kiambu (
Human seroprevalence was generally 2- to 4-folds higher than animal seroprevalence in all the counties. Human and animal seroprevalences were highest in Marsabit County (
On univariate analysis, risk factors identified as significantly (
On univariate analysis, significant factors (
Univariate analysis determining whether animal brucellosis status was associated with human brucellosis at household level was conducted, and results are shown in
This study used a “One Health” approach to simultaneously investigate the prevalence of brucellosis in humans and livestock living in the same households. Although animals are the main reservoirs for human brucellosis, studies on brucellosis have mainly been conducted separately in humans and animals.
Our study found that the odds of human seropositivity were six times higher in households with a seropositive animal compared with those without. Similar findings were reported in a study in Kyrgyzstan.
Household and herd seroprevalence ranged from 5% to 73% and 6% to 68%, respectively, in the three counties with seroprevalence highest in Marsabit. These results are similar to those from another study conducted in Kenya, which reported a cattle seroprevalence ranging from 2% (agricultural high potential area) to 15% (semiarid, pastoralist area).
The high seroprevalence in humans and livestock could reflect the endemicity of brucellosis in some parts of Kenya. Differences in human seroprevalence between the counties are likely due to the predominant production systems. Practices that promote brucellosis transmission such as drinking raw milk, nomadic movements, and use of common grazing and drinking areas for livestock are more likely in the pastoralist communities than agro-based communities.
In this study, the seroprevalence among livestock species was fairly similar within a county, though slightly higher in goats or sheep. This finding could suggest that animal husbandry practices applied in different production systems influence transmission of brucellosis in livestock. In addition, there is possible cross-transmission of multiple
The human individual prevalence of 16% is higher than reported in other community level studies in Egypt (2%),
At the herd level, independent risk factors included keeping goats, keeping sheep, and use of calving pens. Goats and sheep often feed near homesteads where abortions due to brucellosis are likely to happen and could likely be exposed to contaminated environment for longer periods compared with the cattle and camels, increasing the likelihood of infection. Alternatively, goat and sheep could be more susceptible to
At the individual human level, risk factors included increasing age by decade, being male, regularly ingesting raw milk, exposure to goats (herding, milking, and feeding), and handling animal hides. These findings are consistent with findings from other studies, which indicate that the risk of human brucellosis is related to transmission through direct contact with animals or their products or indirectly through consumption of their products.
This study has several limitations. First, the exclusion of children < 5 years of age limits the generalizability of our data to the entire population. Second, our testing methods report apparent rather than true prevalence. However, given the validity of the assays used, this difference is likely minimal. The ELISA tests used detected only antibodies against IgG but not IgM. It is possible that some participants could have had acute infection and be IgM positive but IgG negative, with the potential effect that the prevalence stated could be an underestimate. However, a study on diagnostic methods for brucellosis where IgG and IgM antibodies were measured simultaneously found little difference in the assays.
Our study gives evidence of a strong association between human and animal seropositivity at household level. In particular, goat and camel seropositivity was strongly associated with human seropositivity. There was higher prevalence of brucellosis in human and livestock in the predominantly pastoralist communities. To estimate the burden of brucellosis and identify appropriate interventions, it will be necessary to conduct further research to estimate the incidence of brucellosis with molecular typing of
We thank the Ministry of Health, Ministry of Agriculture, Livestock and Fisheries, the County Governments of Kajiado, Kiambu, and Marsabit Counties, and Kenya Medical Research Institute for their participation in the implementation of the study. Norah Musee, Grace Wanjau, Doris Marwanga, and Linus Ochieng from the CDC-Kenya and KEMRI and Nelson Muriu, Samwel Kadivane from the Field Epidemiology and Laboratory Training Program provided helpful suggestions and administrative and logistic support.
Financial support: Financial support was provided by the U.S. Department of Defense's Defense Threat Reduction Agency and U.S. Centers for Disease Control and Prevention.
Authors' addresses: Eric Mogaka Osoro, Ministry of Health, Preventive and Promotive Health, Nairobi, Kenya, E-mail:
Characteristics of the three study counties, Kenya, 2012–3013
| Kajiado | Kiambu | Marsabit | |
|---|---|---|---|
| Human population | 687,312 | 1,623,282 | 291,166 |
| Human population density per km | 31 | 638 | 4 |
| Livestock population and distribution | 584,044 51.9% cattle, 27.0% sheep, 21.2% goats, 0.02% camels | 1,832,045 22.5% cattle, 39.2% sheep, 38.2% goats, 0.1% camels | 2,731,407 15.5% cattle, 35.1% sheep, 41.9% goats, 7.4% camels |
| Average annual rainfall | 700 mm | 1,000 mm | 100 mm |
| Climate | Semiarid | Tropical wet | Semiarid |
Sociodemographic characteristics of study respondents, 2012–2013
| Characteristic | Kajiado ( | Kiambu ( | Marsabit ( |
|---|---|---|---|
| Sex | |||
| Female | 422 (53.4) | 719 (57.3) | 380 (49.7) |
| Male | 369 (46.6) | 536 (42.7) | 385 (50.3) |
| Mean age (SD) | 34.9 (18.5) | 36.7 (19.2) | 34.3 (19.9) |
| Education level | |||
| No education | 201 (25.4) | 57 (4.5) | 518 (67.7) |
| Primary | 335 (42.4) | 569 (45.3) | 191 (25.0) |
| Secondary | 168 (21.2) | 474 (37.8) | 35 (4.6) |
| Post-secondary | 84 (10.6) | 152 (12.1) | 16 (2.1) |
| Other | 3 (0.4) | 3 (0.2) | 5 (0.7) |
| Occupation | |||
| Works on farm/farmer | 342 (43.2) | 618 (49.2) | 386 (50.5) |
| Salaried, off farm, skilled | 49 (6.2) | 130 (10.4) | 42 (5.5) |
| Housewife | 128 (16.2) | 110 (8.8) | 56 (7.3) |
| Salaried, off farm, unskilled | 18 (2.3) | 103 (8.2) | 89 (11.6) |
| Student | 157 (19.9) | 274 (21.8) | 175 (22.9) |
| Other | 97 (12.3) | 20 (1.6) | 17 (2.2) |
SD = standard deviation.
Seroprevalence of brucellosis at household and herd level, 2012–2013
| Household seroprevalence (95% CI) | Herd seroprevalence (95% CI) | |
|---|---|---|
| All counties | 28.0 (24.1–32.4) | 29.9 (25.8–34.2) |
| Kajiado | 28.6 (21.0–37.7) | 30.3 (23.3–38.5) |
| Kiambu | 5.0 (3.3–7.5) | 5.6 (3.6–9.2) |
| Marsabit | 73.4 (65.6–80.0) | 68.0 (59.8–75.3) |
CI = confidence interval.
Seroprevalence of brucellosis in humans and livestock species by county, 2012–2013
| Seroprevalence | All counties % (95% CI) | Kajiado% (95% CI) | Kiambu % (95% CI) | Marsabit % (95% CI) |
|---|---|---|---|---|
| Human | 16.4 (13.5–19.6) | 15.3 (10.5–21.8) | 2.4 (1.9–3.0) | 46.5 (39.0–54.1) |
| Livestock | 8.0 (6.8–9.4) | 3.3 (2.8–4.1) | 1.2 (1.0–1.5) | 13.5 (11.2–16.2) |
| Cattle | 4.1 (3.4–4.8) | 3.3 (3.0–3.5) | 0.8 (0.5–1.1) | 11.2 (9.2–13.7) |
| Goat | 10.7 (9.3–12.3) | 3.6 (2.7–4.7) | 1.3 (1.0–1.8) | 16.1 (13.9–18.5) |
| Sheep | 7.3 (6.1–8.8) | 3.4 (2.8–4.1) | 2.4 (1.9–3.1) | 11.9 (10.2–13.5) |
| Camel | 11.1 (7.1–17.0) | – | – | 11.1 (9.4–15.0) |
CI = confidence interval.
Multivariate logistic regression analysis of the factors associated with human household and herd seropositivity
| All counties | Kajiado | Marsabit | Kiambu | |||||
|---|---|---|---|---|---|---|---|---|
| aOR (95% CI) | aOR (95% CI) | aOR (95% CI) | aOR (95% CI) | |||||
| Human household positivity | ||||||||
| Pastoral production system | 6.8 (5.3–9.0) | < 0.001 | 2.9 (2.1–4.0) | < 0.001 | – | – | 42.7 (21.1–86.5) | < 0.001 |
| Nomadic movements | 3.4 (2.6–4.3) | < 0.001 | 2.3 (1.7–3.2) | < 0.001 | 5.7 (4.2–7.7) | < 0.001 | – | – |
| Male household head | 3.4 (2.9–3.9) | < 0.001 | 4.5 (3.4–5.9) | 0.005 | 2.5 (2.0–3.0) | < 0.001 | 3.0 (2.0–4.7) | < 0.001 |
| Sold livestock from farm in previous 1 year | 1.7 (1.5–2.0) | < 0.001 | 2.2 (0.9–5.1) | 0.074 | 1.4 (1.0–2.1) | 0.054 | 2.1 (1.4–3.3) | 0.001 |
| Keeping cattle | 0.5 (0.4–0.7) | < 0.001 | 0.6 (0.4–1.0) | 0.048 | 0.9 (0.6–1.3) | 0.487 | 1.1 (0.3–4.0) | 0.891 |
| HHD with at least secondary education | 0.4 (0.3–0.5) | < 0.001 | 0.4 (0.4–0.5) | < 0.001 | 0.4 (0.1–0.6) | 0.001 | 0.5 (0.4–0.7) | 0.001 |
| Herd Seropositivity | ||||||||
| Pastoral production system | 9.8 (5.7–17.0) | < 0.001 | 2.9 (1.1–8.0) | 0.039 | – | – | – | – |
| Keeping goats | 2.1 (1.3–3.7) | 0.011 | 1.8 (0.6–5.6) | 0.274 | 1.3 (0.5–3.6) | 0.607 | 3.1 (1.0–9.7) | 0.048 |
| Keeping sheep | 2.6 (1.6–4.1) | < 0.001 | 2.7 (0.9–7.7) | 0.066 | 4.0 (1.7–9.3) | 0.005 | 3.5 (1.2–10.5) | 0.027 |
| Use of calving pens | 2.0 (1.3–3.2) | 0.005 | 4.4 (1.6–11.6) | 0.007 | 1.5 (0.7–3.4) | 0.246 | 0.2 (0.0–1.8) | 0.045 |
| Exposure to aborted game | 0.3 (0.2–0.6) | < 0.001 | 0.5 (0.2–1.2) | 0.007 | 0.5 (0.2–1.8) | 0.268 | – | – |
aOR = adjusted odds ratio; CI = confidence interval.
Significant risk factors associated with human brucellosis exposure analyzed by multivariate logistic regression
| Combined | Kajiado | Kiambu | Marsabit | |||||
|---|---|---|---|---|---|---|---|---|
| aOR (95% CI) | aOR (95% CI) | aOR (95% CI) | aOR (95% CI) | |||||
| Age by decade | 1.2 (1.1–1.2) | < 0.001 | 1.3 (1.2–1.4) | < 0.001 | 1.6 (1.5–1.6) | < 0.001 | 1.1 (1.0–1.2) | 0.010 |
| Male sex | 1.6 (1.3–2.0) | < 0.001 | 1.0 (0.7–1.4) | 0.832 | 1.3 (0.6–2.7) | 0.479 | 3.0 (2.2–4.0) | < 0.001 |
| Use of milk from own animals | 2.6 (2.0–3.4) | < 0.001 | 2.0 (1.4–3.0) | 0.001 | 1.3 (0.7–2.5) | 0.410 | 3.2 (1.7–5.8) | 0.002 |
| Regular ingestion of raw milk | 3.5 (2.8–4.4) | < 0.001 | 2.7 (1.9–3.9) | < 0.001 | – | – | 0.9 (0.6–1.4) | 0.633 |
| Assist in animal delivery | 1.5 (1.2–2.0) | 0.002 | 1.1 (0.6–2.0) | 0.860 | 1.1 (0.7–11.7) | 0.708 | 1.6 (1.1–2.3) | 0.021 |
| Exposure to sheep | 1.6 (1.3–1.8) | < 0.001 | 3.2 (2.1–5.0) | < 0.001 | 0.6 (0.3–1.2) | 0.135 | 2.0 (1.4–2.8) | 0.002 |
| Exposure to goats | 3.1 (2.5–3.8) | < 0.001 | 1.5 (0.9–2.5) | 0.127 | 0.9 (0.4–1.9) | 0.792 | 2.1 (1.4–3.2) | 0.004 |
| Handling of animal hides | 1.8 (1.5–2.2) | < 0.001 | 1.5 (1.2–2.0) | 0.004 | 83.2 (24.9–278.7) | < 0.001 | 1.4 (1.1–1.8) | 0.005 |
| Secondary education and above | 0.3 (0.3–0.4) | < 0.001 | 0.7 (0.5–0.9) | 0.023 | 0.1 (0.0–0.5) | 0.004 | 1.8 (0.4–7.7) | 0.384 |
aOR = adjusted odds ratio; CI = confidence interval.
Association between human and animal brucellosis seropositivity at household level
| OR | 95% CI | ||
|---|---|---|---|
| Livestock | 6.2 | 5.5–7.1 | < 0.001 |
| Goats | 10.7 | 9.0–12.8 | < 0.001 |
| Sheep | 4.2 | 3.4–5.1 | < 0.001 |
| Cattle | 2.7 | 2.1–3.4 | < 0.001 |
| Camel | 11.0 | 8.3–14.7 | < 0.001 |
CI = confidence interval; OR = odds ratio.