Conceived and designed the experiments: CT RB DF. Performed the experiments: CT RB B. Olack BA LC AA B. Ochieng GB PF JO DF. Analyzed the data: CT BA LC AA B. Ochieng DF. Wrote the paper: CT RB B. Olack BA LC AA B. Ochieng GB JRO PF EM DB JO DF.
The epidemiology of non-Typhi
As part of population-based surveillance among 55,000 persons in malaria-endemic, rural and malaria-nonendemic, urban Kenya from 2006–2009, blood cultures were obtained from patients presenting to referral clinics with fever ≥38.0°C or severe acute respiratory infection. Incidence rates were adjusted based on persons with compatible illnesses, but whose blood was not cultured.
NTS accounted for 60/155 (39%) of blood culture isolates in the rural and 7/230 (3%) in the urban sites. The adjusted incidence in the rural site was 568/100,000 person-years, and the urban site was 51/100,000 person-years. In both sites, the incidence was highest in children <5 years old. The NTS-to-typhoid bacteremia ratio in the rural site was 4.6 and in the urban site was 0.05.
NTS caused the majority of bacteremias in rural Kenya, but typhoid predominated in urban Kenya, which most likely reflects differences in malaria endemicity. Control measures for malaria, as well as HIV, will likely decrease the burden of NTS bacteremia in Africa.
Non-Typhi
We evaluated three years of population-based surveillance on NTS bacteremia from an urban informal settlement in Nairobi and a rural area of western Kenya. Our surveillance highlights stark differences in invasive
The Centers for Disease Control and Prevention's (CDC) International Emerging Infections Program (IEIP) and the Kenya Medical Research Institute (KEMRI) have conducted population-based morbidity surveillance since late 2005 in Asembo, in rural western Kenya and in Kibera, an informal settlement in Nairobi. The surveillance sites and design have been described previously
Study participants receive free medical care for most acute conditions at a single referral health facility centrally-located in each site (Lwak Hospital in Asembo, Tabitha Clinic in Kibera). Patients are examined and diagnosed by clinical officers (similar to physician's assistants). Scannable paper questionnaires (TeleForm®, Cardiff™, California) or computerized databases (GFL Partners, Kenya) are completed on all sick visits, documenting symptoms, health-seeking, physical exam, diagnosis, treatment and outcome. Blood cultures are done on persons meeting one of three case definitions.
Severe acute respiratory illness (SARI), defined in persons ≥5 years old as cough or difficulty breathing and either temperature ≥38.0°C or oxygen saturation <90%, and in children <5 years old as those with clinical pneumonia as defined by WHO's Integrated Management of Childhood Illness
Acute febrile illness, defined as a temperature ≥38.0°C, without SARI or other obvious source (e.g. bloody diarrhea), irrespective of malaria blood smear result (only the first two child and first two adult patients who meet this criteria per day are enrolled).
All patients, regardless of age, admitted for conditions unrelated to injury or obstetrics, at Lwak Hospital. (Tabitha Clinic does not have inpatient capacity.)
In addition, blood smears for malaria are done and read by KEMRI/CDC trained microscopists in the clinics, who undergo regular quality assurance evaluations. Stools are also collected, either in specimen cups or by rectal swabs, on patients with diarrheal illness (≥3 looser-than-normal stools in a 24-hour period), regardless of the presence of bloody diarrhea. Swabs of whole stool and rectal swabs were placed immediately in Cary-Blair transport medium and cooled to 4–8°C in insulated containers and shipped on the same day for immediate processing in KEMRI/CDC laboratories
Community interviewers visit enrolled households every two weeks to inquire about illnesses. Symptoms are recorded and an abbreviated physical exam is done by trained field workers. Participants are asked if and where they sought health care. Using household visit data, we defined SARI as an episode with cough or difficulty breathing and documented fever and defined acute febrile illness as someone with reported fever without cough, difficulty breathing, or bloody diarrhea.
Blood (7–10 ml for adults and 1–3 ml for children) was inoculated into commercially-produced broth bottles (BACTEC Plus™/F Aerobic Plus™ and Peds Plus™/F culture vials, Becton Dickinson, Belgium) and incubated in an automated BACTEC 9050 at 35°C for 1–5 days. Bottles with growth as indicated by an audible alarm were removed, Gram-stained and sub-cultured on standard media for bacteria identification using routine microbiologic techniques
Differences in proportions were assessed by chi-square tests and means by t-tests (Epi-Info™,version 3.4.3). Crude rates were calculated as the number of cases of NTS bacteremia per 100,000 person-years of observation (pyo). Each participating individual contributed person-time according to their dates of residence within the surveillance area from October 1, 2006–September 30, 2009 in Asembo and March 1, 2007–February 28, 2009 in Kibera.
Two adjustments were applied to crude rates. First, a multiplier was included for the percentage of persons visiting the referral clinics that met criteria for blood culture and did not have a culture done. The reasons for not getting cultured included the clinician not recognizing that the patient met the case definition, patient refusal, febrile patients presenting after two febrile persons had already been sampled that day, or an in-patient having already received intravenous antibiotics. The percentage of eligible patients who did not receive a blood culture was calculated separately for five age categories and for each indication for blood culturing. A second adjustment was made based on the percentage of persons identified with each of the indications for blood culture at the household visit who visited clinics other than Lwak or Tabitha for that illness. We assumed that those who visited another clinic for the same syndrome had a comparable severity and spectrum of etiologies to those that visited Lwak or Tabitha. 95% confidence intervals were calculated for crude rates using Fisher's method (PEPI, version 4.0×) and for adjusted rates using the delta method
To estimate NTS bacteremia incidence in HIV-infected persons ≥18 years old in the rural site, we adjusted persons with unknown HIV status by applying the same proportion of HIV-positivity among patients with NTS bacteremia for whom HIV status was known. Population prevalence of HIV by age group was obtained from the home-based HIV testing initiative in the surveillance population in 2008 in which all adults were offered HIV testing (KEMRI/CDC unpublished data). Age-specific HIV prevalence rates were applied to obtain the age-specific person-years denominators. Similar adjustment factors were applied as described above.
The protocol and written informed forms for surveillance and home-based HIV testing were reviewed and approved by the Ethical Review Board of KEMRI and the Institutional Review Board of CDC. For children less than 15 years old, parents, next of kin or guardians gave written informed consent to permit the children's participation in the study. Children aged 7–14 years also were required to give their written assent for participation.
Of 3,578 blood cultures done in the rural site, 155 (4.3%) had a pathogen isolated, of which 60 (38.7%) were NTS, the most common bacteria isolated, followed by
| Age in years | 0–4 | 5–9 | 10–17 | 18–49 | >50 | Total |
| 12,698 | 6,292 | 7,249 | 9,840 | 3,940 | 40,019 | |
| 1,647(13.0) | 708(11.3) | 372 (5.1) | 656 (6.7) | 195(4.9) | 3,578 (8.9) | |
| 43(2.6) | 13(1.8) | 11 (3.0) | 67(9.3) | 18(9.2) | 155 (4.3) | |
| 28 (65.1) | 6 (46.2) | 1 (9.1) | 19(28.4) | 6(33.3) | 60 | |
| 4/20 (20.0) | 1/6 (16.7) | 1/1(100) | 9/11(81.8) | 3/4 (75.0) | 18/42 (42.9) | |
| 18,315 | 5,314 | 2,744 | 11,185 | 775 | 38,333 | |
| 1,024(5.6) | 452 (8.5) | 193(7.0) | 447(4.0) | 22(2.8) | 2,138(5.6) | |
| 69(6.7) | 76 (16.8) | 33(17.1) | 51(11.4) | 1(4.5) | 230 (10.8) | |
| 5(7.2) | 1(1.3) | 0 (0) | 1(2.0) | 0(0.0) | 7 (3.0) | |
One patient, an HIV-positive individual, had a recurrence of NTS bacteremia infection after one month in the rural site.
0 of 1 (0%) adult with NTS was HIV-positive in Kibera.
The predominant serotype of
| Age category | Rural Kenya | Urban Kenya | ||
| NTS Cases | 28 | NTS Cases | 5 | |
| Typhi Cases | 1 | Typhi Cases | 35 | |
| NTS: Typhi ratio | 28.0 | NTS: Typhi ratio | 0.14 | |
| NTS Cases | 32 | NTS Cases | 2 | |
| Typhi Cases | 12 | Typhi Cases | 100 | |
| NTS: Typhi ratio | 2.67 | NTS: Typhi ratio | 0.02 | |
There was a broader distribution of NTS serotypes in stool than blood (
Chl is chloramphenicol, sxt is trimethoprim-sulfamethoxazole, Tetr is tetracycline, Cip is ciprofloxacin, Nal is nalidixic acid, Amp is ampicillin, Sxz is sulfisoxazole, Strep is streptomycin, Kan is kanamycin, Genta is gentamycin, Ctx is ceftriazone, Amc is amoxicillin-clavulinic acid, Multi Drug Resistance (MDR) defined as resistance to chloramphenicol, trimethoprim-sulfamethoxazole and ampicillin.
| Category | Rural Kenya | Urban Kenya | ||
| (n = 60) | (n = 7) | |||
| Serotype | Number (%) | Serotype | Number (%) | |
| Typhimurium | 53 (88.3%) | Typhimurium | 6 (85.7%) | |
| Enteritidis | 6 (10.0%) | Enteritidis | 1 (14.3%) | |
| Heidelberg | 1 (1.7%) | |||
| (n = 33) | (n = 14) | |||
| Serotype | Number (%) | Serotype | Number (%) | |
| Typhimurium | 21 (63.6%) | Enteritidis | 4 (28.6%) | |
| Enteritidis | 3 (9.1%) | Typhimurium | 3 (21.4%) | |
| Virchow | 3 (9.1%) | Virchow | 1 (7.1%) | |
| Heidelberg | 2 (6.1%) | Heidelberg | 1 (7.1%) | |
| Newport | 2 (6.1%) | Muenchen | 1 (7.1%) | |
| Aberdeen | 1 (3.0%) | Agona | 1 (7.1%) | |
| Chailey | 1 (3.0%) | Stanleville | 1 (7.1%) | |
| Haifa | 1 (7.1%) | |||
| Bovismorbificans | 1 (7.1%) | |||
There was no clear seasonal pattern to NTS bacteremia in either site. In the rural site, a concomitant increase in the number of NTS bacteremia cases and positive malaria cases was observed in 2008–9 (
A. All persons (spearman rank correlation coefficient, 0.87, p = 0.0003). B. Children <5 years old (spearman rank correlation coefficient, 0.66, p = 0.018). C. Persons ≥5 years of age (spearman rank correlation coefficient, 0.43, p = 0.18).
In the rural site, 18 (43%) of 42 patients with NTS bacteremia whose HIV status was known were HIV-positive (
Overall crude and adjusted NTS incidence was higher in rural Kenya (78 per 100,000 pyo and 580 per 100,000 pyo, respectively) than in urban Kenya (13 per 100,000 pyo and 57 per 100,000 pyo, respectively) (
| AgeIn years | Site | NTS(n) | Pyo | Crude Rate per 100,000 Pyo(95% CI) | Rate Extrapolation 1 | Rate Extrapolation 2 |
| Rural | 28 | 13,572 | 206 (138–298) | 759 (542–916) | 2085 (1181–2990) | |
| Urban | 5 | 9,595 | 52 (17–122) | 208 (95–322) | 260 (102–419) | |
| Rural | 6 | 11,312 | 53 (19–115) | 150 (82–218) | 389 (106–672) | |
| Urban | 1 | 8,049 | 12 (0.12–92) | 25 (5–44) | 37 (1–73) | |
| Rural | 1 | 16,756 | 6.0 (0.18–33) | 18 (0–43) | 24 (0–62) | |
| Urban | 0 | 8,017 | 0 (0–46) | 0 (NA) | 0 (NA) | |
| Rural | 19 | 25,015 | 76 (46–119) | 155 (106–206) | 367 (186–550) | |
| Urban | 1 | 26,752 | 3.7 (0.15–27) | 7.5 (0–18) | 11.2 (0–31) | |
| Rural | 6 | 10362 | 58 (21–126) | 145 (86–204) | 232 (112–351) | |
| Urban | 0 | 2,120 | 0 (0–174) | 0 (NA) | 0 (NA) | |
| Rural | ||||||
| Urban |
*Pyo = person-years of observation.
**Extrapolated for patients meeting indication for blood culture who were not cultured in the clinic.
***Extrapolated for patients meeting indication for blood culture who were not cultured in the clinic and those with same illness syndromes at the home visit who sought care at area clinics besides Lwak and Tabitha clinics.
Among the 7 NTS-associated deaths (2 children and 5 older persons), 1 occurred in the first 30 days after the date of the positive blood culture, 3 died from 31–60 days, and 3 died from 61–90 days afterwards. The 30-day case-fatality ratio (CFR) was 0% for children and 3.1% for older persons; the 90-day CFR was 7.1% for children and 15.6% for older persons. Compared with patients of the same age group who had a blood smear positive for malaria, but were not bacteremic, the 90 day mortality among NTS bacteremia cases in the rural Kenya site was 9 times higher for patients <5 years old and 68 times higher for patients ≥5 years old (
| Age | NTS cases 90 day mortality rate (per 1,000 pyo) | B/S Positive malaria cases 90 day mortality rate (per 1,000 pyo) | Risk Ratio for 90 day mortality NTS: Malaria (95% CI) | Non-NTS bacteremia 90 day mortality rate (per 1,000 pyo) | Risk Ratio for 90 day mortality NTS: Other pathogen (95% CI) |
| <5 Years | 298 | 33 | 9.0 (2.4–37) | 288 | 1.0 (0.14–7.9) |
| >5 Years | 683 | 10 | 67 (26–172) | 491 | 1.39 (0.49–4.0) |
There were no NTS related deaths reported in the urban area during the study period.
90-day mortality rate calculated as deaths in the 90 days after positive blood culture or malaria blood smear, annualized to 1,000 person-years of observation.
NTS was the leading isolate from bloodstream infections in rural Kenya, with incidence in the higher range of those found in other rural African settings, where rates ranged from 88–330 cases per 100,000 pyo
Besides malaria, there are several other reasons for the rural/urban difference in invasive
The high burden of NTS in adults in the rural site is also influenced by the high prevalence of HIV, as has been shown in other African settings
We found a lower mortality from episodes of NTS bacteremia than other studies. Because free, high-quality care was offered to surveillance participants, ill persons likely came to the clinic at earlier stages of illness, so that milder cases of NTS bacteremia might have been captured, as suggested by the observation that 62% of NTS bacteremia patients in the rural site were treated as outpatients. Most studies have been done among hospitalized patients, where case-fatality rates for NTS bacteremia were much higher than we found, ranging from 4–27% for children and from 22–47% for adults
Our study had several limitations. First, in making adjustments of bacteremia rates, we made certain assumptions – NTS isolation rates would be the same among those meeting indications for blood culture who did not get cultured and that those patients under surveillance who attended another clinic for their illness would also have similar isolation rates to those who went to Lwak and Tabitha. Both assumptions might be subject to biases. Nonetheless, the crude rates are clearly an underestimate of the true rate in the community, due to limited health-care utilization and insensitivity of blood cultures, and the adjustments provide reasonable upward adjustments, although should be considered the maximal rate. Second, only 60% of patients with NTS bacteremia had a confirmed HIV status and we assumed that those not tested had the same proportion HIV-positive as those tested. This assumption also might have been subject to differential bias. Third, NTS is a more robust and antibiotic resistant than the more fastidious Gram-positive bacteria, particularly
Regardless of these limitations, NTS bacteremia clearly continues to cause a substantial burden of morbidity among children and HIV-infected adults in rural Kenya, warranting further investigation to define amenable risk factors, best treatment guidelines and new interventions, such as NTS vaccines currently under development
We thank the people of Asembo and Kibera for their continued support and cooperation with KEMRI/CDC. We thank the verbal autopsy team of the KEMRI/CDC Health and Demographic Surveillance System. This paper is published with the permission of the director of the Kenya Medical Research Institute. The findings and conclusions are those of the authors and do not necessarily represent the views of the Centers for Disease Control and Prevention.