Analysis of small ruminants’ pastoral management practices as risk factors of peste des petits ruminants (PPR) spread in Turkana District, Kenya

Peste des petits ruminants (PPR) is an emerging viral disease spreading throughout Kenya and East Africa causing major losses in the small stock. This study is an attempt to evaluate small stock management practices in Turkana pastoral system, Kenya as predictors of PPR outbreaks. Information on the social practices and the occurrence of PPR outbreaks was obtained by participatory techniques. The small stock management practices, evaluated as factors, in a previous study were simultaneously analyzed with seasons and administrative divisions as the independent risk factors for the presence or absence of PPR outbreaks in 142 Adakars (villages) as the dependent variable. Analyses were carried out for the years 2009 and 2010 combined as one data set and considered as longitudinal repeated data. In the analyses, the presence or absence of PPR outbreaks was the dependent variable. Data were further analyzed separately disaggregated by season where the presence or absence of PPR outbreaks in a season was considered as the dependent variable. All analyses utilized multivariable logistical regression analyses. In the longitudinal analysis, season was the only significant factor associated with PPR outbreak. Disaggregating the data by season revealed that certain seasonal-specific livestock management activities increased the risk of reporting PPR outbreaks: (1) sharing water sources leading to social aggregation of young stock in one point (Factor 3) (odds ratio (OR) = 2.0) in season 2 (wet season) of 2009; (2) sick dams left to nurse their young kids/lambs (Factor 7) (OR=1.62) in the same season in 2010. The finding of diverse risk factors in the same seasons across years suggests temporal heterogeneity in the distribution and occurrence of the determinants of PPR in the Turkana ecosystem. The study discusses the implications of these findings on disease control

UK vaccines network:Mapping priority pathogens of epidemic potential and vaccine pipeline developments

During the 2013–2016 Ebola outbreak in West Africa an expert panel was established on the instructions of the UK Prime Minister to identify priority pathogens for outbreak diseases that had the potential to cause future epidemics. A total of 13 priority pathogens were identified, which led to the prioritisation of spending in emerging diseases vaccine research and development from the UK. This meeting report summarises the process used to develop the UK pathogen priority list, compares it to lists generated by other organisations (World Health Organisation, National Institutes of Allergy and Infectious Diseases) and summarises clinical progress towards the development of vaccines against priority diseases. There is clear technical progress towards the development of vaccines. However, the availability of these vaccines will be dependent on sustained funding for clinical trials and the preparation of clinically acceptable manufactured material during inter-epidemic periods

Theileria parva infection seroprevalence and associated risk factors in cattle in Machakos County, Kenya

The principle objective of this study was to estimate the infection seroprevalence and identify risk factors associated with Theileria parva infection in cattle on smallholder farms in Machakos County, Kenya. A total of 127 farms were selected by a proportional allocation approach based on the number of farms in four divisions in the county previously selected by stratified random sampling method. Subsequently, a total sample of 421 individual animals was randomly selected from the farms. Information on animal and relevant individual farm management practices was gathered using a standardized questionnaire. Prevalence of serum antibodies was determined using the enzyme-linked immunosorbent assay (ELISA). Multivariable logistic models incorporating random effects at the farm level evaluated the association between the presence of T. parva antibodies and the identified risk variables. The overall estimation of T. parva antibodies in the county was 40.9 % (95 % confidence interval of 36.1, 45.7 %). Seroprevalence to T. parva was significantly associated with animal age, vector tick infestation in the animal, tick control frequency, and administrative division. Further analyses suggested a confounding relationship between administrative division and both breed and grazing system and the T. parva seropositivity. Random effects model yielded intra-farm correlation coefficient (ICC) of 0.18. The inclusion of farm random effect provided a substantially better fit than the standard logistic regression (P = 0.032). The results demonstrate substantial variability in the T. parva infection prevalence within all categories of the cattle population of Machakos County of Kenya, where East Coast fever is endemic

Prognostic indicators of post partum viability of kids born to Escherichia coli-vaccinated or unvaccinated does : research communication

This study was undertaken to determine some blood and other physiological parameters with potential for use as prognostic indicators of viability of newborn goat kids. Of the 143 kids born during the on-farmstudy, 97 were crosses of Galla × Small East African (SEA) and 46 were pure SEA. The SEA × Galla kids were 46 single males, with a mean body weight at birth of 2.77 ± 0.22 kg , 43 females with a mean body weight at birth of 2.36 ± 0.76 kg and 5 and 3 sets of female and male twins (mean body weight at birth of 1.8 ± 0.19 kg and 2.05 ± 0.07 kg for the female and male kids, respectively). The SEA kids comprised 36 single male and female kids (mean body weight at birth of 2.48 ± 0.04 kg and 10 sets of twins (both male and female) (mean body weight at birth of 1.50 ± 0.04 kg ). Pre-suckling sera obtained on-station from kids born of does vaccinated against Escherichia coli (n = 8) and unvaccinated does (n = 7) had a total protein content of < 40.0 g/l and no detectable levels of IgG and A or E. coli antibodies. Sera obtained 12 hours post partum from kids that survived in both groups contained about 19-22 g of Ig g/ , 50-80 g total protein/ , blood glucose of >5 mmol/l and had an E. coli antibody titre of between 1/160 and 1/640. On the other hand, kids that died within 48 hours of birth (parturient deaths) and had been classified in categories 3 and 4 righting reaction had low (< 40 g//l ) total protein, low white blood cell count (4000/m/l ) and low blood glucose concentration (< 4.9 mmol//l ). It is concluded that kids with delayed righting reaction (> 45 minutes), low rectal temperature (< 36 °C), low birth weights (< 1.5 kg for singles and < 1.0 kg for twins), low white blood cells (< 4000/ m/l ), low (< 2 mmol/l ) blood glucose levels, low total protein (< 40.0 g//l ), low (< 1:160) E. coli antibody titre and IgG ( < 3350 mg//l ) in sera obtained 12 hours after birth have a poor prognosis for survival

Sero-epidemiology of Peste des petits ruminants virus infection in Turkana County, Kenya

Background Peste des petits ruminants (PPR) is a contagious viral disease of small ruminants. Serum samples from sheep (n = 431) and goats (n = 538) of all ages were collected in a cross-sectional study in Turkana County, Kenya. The objective was to estimate the sero-prevalence of PPR virus (PPRV) infection and associated risk factors in both species. PPRV competitive enzyme-linked immuno-sorbent assay (c-ELISA) analysed the presence of antibodies in the samples. All analyses were conducted for each species separately. Multivariable logistic regression models were fitted to the data to assess the relationship between the risk factors and PPRV sero-positivity. Mixed-effect models using an administrative sub-location as a random effect were also fitted to adjust for possible clustering of PPRV sero-positivity. Intra-cluster correlation coefficients (ρ) that described the degree of similarity among sero-positive responses for each species in each of the six administrative divisions were estimated. Results Goats had a significantly higher sero-prevalence of 40% [95% confidence interval (CI): 36%, 44%] compared to sheep with 32% [95% CI: 27%, 36%] (P = 0.008). Combined sero-prevalence estimates were heterogeneous across administrative divisions (n = 6) (range 22% to 65%) and even more across sub-locations (n = 46) (range 0% to 78%). Assuming that PPRV antibodies are protective of infection, a large pool of PPRV susceptible middle age group (>6 months and < 24 months) in both species was estimated. This was based on the low sero-prevalence in this group in goats (14% [95% CI: 10%, 20%]) and in sheep (18% [95% CI: 13%, 25%]). Regression analysis returned significant risk factors across species: in sheep - vaccination status, age and administrative division; in goats - sex, age, administrative division and sex*age interaction. The intra-sub-location correlation coefficients varied widely across divisions (range <0.001 to 0.42) and across species within divisions. Conclusions Biological, spatial and socio-ecological factors are hypothesized as possible explanations for variation in PPRV sero-positivity in the Turkana pastoral ecosystem

Associations between schistosomiasis and HIV-1 acquisition risk in four prospective cohorts: a nested case-control analysis

Introduction Globally, schistosomes infect approximately 200 million people, with 90% of infections in sub-Saharan Africa. Schistosomiasis is hypothesized to increase HIV-1 acquisition risk, and multiple cross-sectional studies reported strong associations. We evaluated this hypothesis within four large prospective cohorts. Methods We conducted nested case-control analyses within three longitudinal cohorts of heterosexual HIV-1 serodiscordant couples and one female sex worker (FSW) cohort from Kenya and Uganda. The serodiscordant couples studies were conducted between 2004 and 2012 while the FSW cohort analysis included participant follow-up from 1993 to 2014. Cases HIV-1 seroconverted during prospective follow-up; three controls were selected per case. The presence of circulating anodic antigen in archived serum, collected prior to HIV-1 seroconversion, identified participants with active schistosomiasis; immunoblots determined the schistosome species. Data from serodiscordant couples cohorts were pooled, while the FSW cohort was analysed separately to permit appropriate confounder adjustment. Results We included 245 HIV-1 seroconverters and 713 controls from the serodiscordant couples cohorts and 330 HIV-1 seroconverters and 962 controls from the FSW cohort. The prevalence of active schistosomiasis was 20% among serodiscordant couples and 22% among FSWs. We found no association between schistosomiasis and HIV-1 acquisition risk among males (adjusted odds ratio (aOR) = 0.99, 95% CI 0.59 to 1.67) or females (aOR = 1.21, 95% CI 0.64 to 2.30) in serodiscordant couples. Similarly, in the FSW cohort we detected no association (adjusted incidence rate ratio (aIRR) = 1.11, 95% CI 0.83 to 1.50). Exploring schistosome species-specific effects, there was no statistically significant association between HIV-1 acquisition risk andSchistosoma mansoni(serodiscordant couples: aOR = 0.90, 95% CI 0.56 to 1.44; FSW: aIRR = 0.83, 95% CI 0.53 to 1.20) orSchistosoma haematobium(serodiscordant couples: aOR = 1.06, 95% CI 0.46 to 2.40; FSW: aIRR = 1.64, 95% CI 0.93 to 2.87) infection. Conclusions Schistosomiasis was not a strong risk factor for HIV-1 acquisition in these four prospective studies.S. mansoniwas responsible for the majority of schistosomiasis in these cohorts, and our results do not support the hypothesis thatS. mansoniinfection is associated with increased HIV-1 acquisition risk.S. haematobiuminfection was associated with a point estimate of elevated HIV-1 risk in the FSW cohort that was not statistically significant, and there was no trend towards a positive association in the serodiscordant couples cohorts.Host-parasite interactio

Schistosomiasis was not associated with higher HIV-1 plasma or genital set point viral loads among HIV seroconverters from four cohort studies

Author summary Schistosomiasis is a parasitic disease that is common in many parts of sub-Saharan Africa most affected by the HIV-1 epidemic. Schistosomiasis causes genital damage when schistosome ova become lodged in the female genital tract, inducing inflammation that may elevate HIV-1 genital viral loads and increase the risk of HIV-1 transmission. Schistosomiasis may also promote viral replication by facilitating cell-to-cell transmission of HIV-1, elevating HIV-1 plasma viral load levels. Using data from 370 individuals residing in Kenya or Uganda who acquired HIV-1 while participating in one of four prospective cohort studies, we tested the hypotheses that schistosomiasis increases plasma and genital viral load levels. We found no evidence that individuals with schistosomiasis had higher set point plasma viral load levels, a measure of viral replication obtained during the set point period 4-24 months after HIV-1 acquisition when viral load levels remain relatively stable. Additionally, we found no evidence that schistosomiasis was associated with higher female set point genital viral loads measured from vaginal or cervical swabs. Unexpectedly, we found that S. mansoni infection was associated with a decline in plasma viral load levels while S. haematobium infection was associated with a decline in cervical viral load levels. Thus, our results do not support the hypotheses that schistosomiasis increases plasma and genital HIV-1 viral loads.Background Many regions of sub-Saharan Africa experience a high prevalence of both schistosomiasis and HIV-1, leading to frequent coinfection. Higher plasma HIV-1 viral loads are associated with faster disease progression and genital HIV-1 loads are a primary determinant of HIV-1 transmission risk. We hypothesized that schistosome infection would be associated with higher HIV-1 viral loads in plasma and genital samples. Methods/Principal findings We utilized data from individuals who HIV-1 seroconverted while enrolled in one of four prospective cohort studies. Plasma and genital viral loads collected 4-24 months after the estimated date of HIV-1 acquisition, but prior to antiretroviral therapy initiation, were included. Detection of circulating anodic antigen in archived blood samples, collected prior to HIV-1 seroconversion, identified participants with active schistosomiasis; immunoblots determined the schistosome species causing infection. Our analysis included 370 HIV-1 seroconverters with plasma viral load results, of whom 82 (22%) had schistosomiasis. We did not find a statistically significant association between schistosomiasis and higher HIV-1 set point plasma viral loads (-0.17 log(10) copies/ml, 95% CI -0.38 to 0.03); S. mansoni infection was associated with a lower set point (-0.34 log(10) copies/ml, 95% CI -0.58 to -0.09). We found no association between schistosomiasis and cervical (+0.07 log(10) copies/swab, 95% CI -0.20 to 0.34) or vaginal (+0.11 log(10) copies/swab, 95% CI -0.17 to 0.39) set point viral loads; S. haematobium infection was associated with lower cervical viral loads (-0.59 log(10) copies/swab, 95% CI -1.11 to -0.06).Host-parasite interactio

Imported SARS-CoV-2 variants of concern drove spread of infections across Kenya during the second year of the pandemic

Using classical and genomic epidemiology, we tracked the COVID-19 pandemic in Kenya over 23 months to determine the impact of SARS-CoV-2 variants on its progression. SARS-CoV-2 surveillance and testing data were obtained from the Kenya Ministry of Health, collected daily from 306 health facilities. COVID-19-associated fatality data were also obtained from these health facilities and communities. Whole SARS-CoV-2 genome sequencing were carried out on 1241 specimens. Over the pandemic duration (March 2020–January 2022), Kenya experienced five waves characterized by attack rates (AR) of between 65.4 and 137.6 per 100,000 persons, and intra-wave case fatality ratios (CFR) averaging 3.5%, two-fold higher than the national average COVID-19 associated CFR. The first two waves that occurred before emergence of global variants of concerns (VoC) had lower AR (65.4 and 118.2 per 100,000). Waves 3, 4, and 5 that occurred during the second year were each dominated by multiple introductions each, of Alpha (74.9% genomes), Delta (98.7%), and Omicron (87.8%) VoCs, respectively. During this phase, government-imposed restrictions failed to alleviate pandemic progression, resulting in higher attack rates spread across the country. In conclusion, the emergence of Alpha, Delta, and Omicron variants was a turning point that resulted in widespread and higher SARS-CoV-2 infections across the country

The ASOS Surgical Risk Calculator: development and validation of a tool for identifying African surgical patients at risk of severe postoperative complications

Background: The African Surgical Outcomes Study (ASOS) showed that surgical patients in Africa have a mortality twice the global average. Existing risk assessment tools are not valid for use in this population because the pattern of risk for poor outcomes differs from high-income countries. The objective of this study was to derive and validate a simple, preoperative risk stratification tool to identify African surgical patients at risk for in-hospital postoperative mortality and severe complications. Methods: ASOS was a 7-day prospective cohort study of adult patients undergoing surgery in Africa. The ASOS Surgical Risk Calculator was constructed with a multivariable logistic regression model for the outcome of in-hospital mortality and severe postoperative complications. The following preoperative risk factors were entered into the model; age, sex, smoking status, ASA physical status, preoperative chronic comorbid conditions, indication for surgery, urgency, severity, and type of surgery. Results: The model was derived from 8799 patients from 168 African hospitals. The composite outcome of severe postoperative complications and death occurred in 423/8799 (4.8%) patients. The ASOS Surgical Risk Calculator includes the following risk factors: age, ASA physical status, indication for surgery, urgency, severity, and type of surgery. The model showed good discrimination with an area under the receiver operating characteristic curve of 0.805 and good calibration with c-statistic corrected for optimism of 0.784. Conclusions: This simple preoperative risk calculator could be used to identify high-risk surgical patients in African hospitals and facilitate increased postoperative surveillance. © 2018 British Journal of Anaesthesia. Published by Elsevier Ltd. All rights reserved.Medical Research Council of South Africa gran