Development of emergency medicine in Rwanda

AbstractRwanda, known as the “Land of a Thousand Hills,” is a small, East African country that was the site of the devastating 1994 genocide. In the past 18years, this post-conflict country has made tremendous progress in rebuilding itself and its health infrastructure. The country has recovered or surpassed many of its pre-1994 health levels, including reduction in HIV/AIDS prevalence, under-five mortality and road traffic accidents. Nevertheless, Rwanda continues to face a high burden of disease. The leading causes of mortality in Rwanda include complications of HIV/AIDS and related opportunistic infections, severe malaria, pulmonary infections, and trauma, and are best managed with emergency and acute care services. However, health care personal resources remain significantly lacking, and there is currently no emergency medicine-trained workforce.The Rwandan government, partnering with international organizations, has launched a campaign to improve human resources for health, and as a part of that effort the creation of training programs in emergency medicine is now underway. The Rwandan Human Resources for Health program can serve as a guide to the development of similar programs within other African countries. The emergency medicine component of this program includes two tracks: a 2-year postgraduate diploma course, followed by a 3-year Masters of Medicine in Emergency Medicine. The program is slated to graduate its first cohort of trained Emergency Physicians in 2017

The use of cannabis seeds as a natural contraceptive: a case of Zambia

The link between population growth or fertility rates and socio-economic development is unquestionable, hence, the increasing call for more investment in family planning programs and research. Zambia is a country in Sub-Sahara Africa with one of the highest fertility rates in the world, high unmet need for modern contraceptives, high rate of teenage pregnancy, high HIV/AIDS prevalence rate, high occurrence of early marriages and a predominantly young population. In response to this harsh reality, the Zambian government is determined to transform the economy by taking advantage of the opportunity that this demographic dividend presents

Profile: The Kilifi Health and Demographic Surveillance System (KHDSS).

The Kilifi Health and Demographic Surveillance System (KHDSS), located on the Indian Ocean coast of Kenya, was established in 2000 as a record of births, pregnancies, migration events and deaths and is maintained by 4-monthly household visits. The study area was selected to capture the majority of patients admitted to Kilifi District Hospital. The KHDSS has 260 000 residents and the hospital admits 4400 paediatric patients and 3400 adult patients per year. At the hospital, morbidity events are linked in real time by a computer search of the population register. Linked surveillance was extended to KHDSS vaccine clinics in 2008. KHDSS data have been used to define the incidence of hospital presentation with childhood infectious diseases (e.g. rotavirus diarrhoea, pneumococcal disease), to test the association between genetic risk factors (e.g. thalassaemia and sickle cell disease) and infectious diseases, to define the community prevalence of chronic diseases (e.g. epilepsy), to evaluate access to health care and to calculate the operational effectiveness of major public health interventions (e.g. conjugate Haemophilus influenzae type b vaccine). Rapport with residents is maintained through an active programme of community engagement. A system of collaborative engagement exists for sharing data on survival, morbidity, socio-economic status and vaccine coverage

The impact of the COVID-19 pandemic on vaccine coverage in Kilifi, Kenya: A retrospective cohort study.

The COVID-19 pandemic caused unprecedented disruption in health service delivery, globally. This study sought to provide evidence on the impact of the pandemic on vaccine coverage in Kilifi County, Kenya. We conducted a vaccine coverage survey between April and June 2021 within the Kilifi Health and Demographic Surveillance System (KHDSS). Simple random sampling was used to identify 1500 children aged 6 weeks-59 months. Participants were grouped into three retrospective cohorts based on when they became age-eligible for vaccination: before the pandemic, during the first year, or during the second year of the pandemic. Survival analysis with Cox regression was used to evaluate the association between the time-period at which participants became age-eligible for vaccination and the rate of vaccination within a month of age-eligibility for the third dose of pentavalent vaccine (Pentavalent-3) and within three months of age-eligibility for the first dose of Measles vaccine (MCV-1). A total of 1,341 participants were included in the survey. Compared to the pre-COVID-19 baseline period, the rate of vaccination within a month of age-eligibility for Pentavalent-3 was not significantly different in the first year of the pandemic (adjusted hazard ratio [aHR] 1.03, 95 % confidence interval [CI] 0.90-1.18) and was significantly higher during the second year of the pandemic (aHR 1.33, 95 % CI 1.07-1.65). The rate of vaccination with MCV-1 within three months of age-eligibility was not significantly different among those age-eligible for vaccination during the first year of the pandemic (aHR 1.04, 95 % CI 0.88-1.21) and was 35 % higher during the second year of the pandemic (95 % CI 1.11-1.64), compared to those age-eligible pre-COVID-19. After adjusting for known determinants of vaccination, the COVID-19 pandemic did not adversely affect the rate of vaccination within the KHDSS

Safety and immunogenicity of Rift Valley fever MP-12 and arMP-12ΔNSm21/384 vaccine candidates in goats (Capra aegagrus hircus) from Tanzania

Vaccination of domestic ruminants is considered to be an effective strategy for protecting these animals against Rift Valley fever (RVF), but available vaccines have limitations. Therefore, the aim of this study was to determine the safety and immunogenicity of RVF virus (RVFV) mutagenesis passage 12 (MP-12) and arMP-12ΔNSm21/384 vaccine candidates in goats (Capra aegagrus hircus) in Tanzania. Goats were vaccinated intramuscularly with RVFV MP-12 or arMP-12ΔNSm21/384, and then on Day 87 post-vaccination (PV) all animals were revaccinated using the RVFV MP-12 vaccine candidate. Serum samples were collected from the animals before and after vaccination at various intervals to test for RVFV using a Vero cell culture assay and reverse transcription polymerase chain reaction and for RVFV-neutralising antibody using a plaque reduction neutralisation assay. Serum samples collected before vaccination on Days -14 and 0, and on Days 3, 4 and 5 PV were negative for RVFV and neutralising antibody. All animals remained healthy, and viremia was not detected in any of the animals. Rift Valley fever virus antibody was first detected on Day 5 PV at a 1:10 dilution in five of five animals vaccinated with the MP-12 vaccine and in five of eight animals vaccinated with arMP-12ΔNSm21/384. Titres then increased and were sustained at 1:40 to 1:640 through to Day 87 PV. All animals that were revaccinated on Day 87 PV with MP-12 developed antibody titres ranging from 1:160 to as high as 1:10 240 on Days 14 and 21 PV. Although the antibody titres for goats vaccinated with RVF MP-12 were slightly higher than titres elicited by the arMP-12ΔNSm21/384 vaccine, these findings demonstrated that both vaccines are promising candidates for the prevention of RVF among Tansanian goats

Gametocyte carriage in an era of changing malaria epidemiology: A 19-year analysis of a malaria longitudinal cohort

Background: Interventions to block malaria transmission from humans to mosquitoes are currently in development. To be successfully implemented, key populations need to be identified where the use of these transmission-blocking and/or reducing strategies will have greatest impact. Methods: We used data from a longitudinally monitored cohort of children from Kilifi county located along the Kenyan coast collected between 1998-2016 to describe the distribution and prevalence of gametocytaemia in relation to transmission intensity, time and age. Data from 2,223 children accounting for 9,134 person-years of follow-up assessed during cross-sectional surveys for asexual parasites and gametocytes were used in logistic regression models to identify factors predictive of gametocyte carriage in this cohort. Results: Our analysis showed that children 1-5 years of age were more likely to carry microscopically detectable gametocytes than their older counterparts. Carrying asexual parasites and recent episodes of clinical malaria were also strong predictors of gametocyte carriage. The prevalence of asexual parasites and of gametocyte carriage declined over time, and after 2006, when artemisinin combination therapy (ACT) was introduced, recent episodes of clinical malaria ceased to be a predictor of gametocyte carriage.  Conclusions: Gametocyte carriage in children in Kilifi has fallen over time.  Previous episodes of clinical malaria may contribute to the development of carriage, but this appears to be mitigated by the use of ACTs highlighting the impact that gametocidal antimalarials can have in reducing the overall prevalence of gametocytaemia when targeted on acute febrile illness.</ns4:p

Age-dependent acquisition of IgG antibodies to Shigella serotypes—a retrospective analysis of seroprevalence in Kenyan children with implications for infant vaccination

BackgroundShigellosis mainly affects children under 5 years of age living in low- and middle-income countries, who are the target population for vaccination. There are, however, limited data available to define the appropriate timing for vaccine administration in this age group. Information on antibody responses following natural infection, proxy for exposure, could help guide vaccination strategies.MethodsWe undertook a retrospective analysis of antibodies to five of the most prevalent Shigella serotypes among children aged &lt;5 years in Kenya. Serum samples from a cross-sectional serosurvey in three Kenyan sites (Nairobi, Siaya, and Kilifi) were analyzed by standardized ELISA to measure IgG against Shigella sonnei and Shigella flexneri 1b, 2a, 3a, and 6. We identified factors associated with seropositivity to each Shigella serotype, including seropositivity to other Shigella serotypes.ResultsA total of 474 samples, one for each participant, were analyzed: Nairobi (n = 169), Siaya (n = 185), and Kilifi (n = 120). The median age of the participants was 13.4 months (IQR 7.0–35.6), and the male:female ratio was 1:1. Geometric mean concentrations (GMCs) for each serotype increased with age, mostly in the second year of life. The overall seroprevalence of IgG antibodies increased with age except for S. flexneri 6 which was high across all age subgroups. In the second year of life, there was a statistically significant increase of antibody GMCs against all five serotypes (p = 0.01–0.0001) and a significant increase of seroprevalence for S. flexneri 2a (p = 0.006), S. flexneri 3a (p = 0.006), and S. sonnei (p = 0.05) compared with the second part of the first year of life. Among all possible pairwise comparisons of antibody seropositivity, there was a significant association between S. flexneri 1b and 2a (OR = 6.75, 95% CI 3–14, p &lt; 0.001) and between S. flexneri 1b and 3a (OR = 23.85, 95% CI 11–54, p &lt; 0.001).ConclusionChildren living in low- and middle-income settings such as Kenya are exposed to Shigella infection starting from the first year of life and acquire serotype-specific antibodies against multiple serotypes. The data from this study suggest that Shigella vaccination should be targeted to infants, ideally at 6 or at least 9 months of age, to ensure children are protected in the second year of life when exposure significantly increases

Identifying children with excess malaria episodes after adjusting for variation in exposure: identification from a longitudinal study using statistical count models

BACKGROUND: The distribution of Plasmodium falciparum clinical malaria episodes is over-dispersed among children in endemic areas, with more children experiencing multiple clinical episodes than would be expected based on a Poisson distribution. There is consistent evidence for micro-epidemiological variation in exposure to P. falciparum. The aim of the current study was to identify children with excess malaria episodes after controlling for malaria exposure. METHODS: We selected the model that best fit the data out of the models examined and included the following covariates: age, a weighted local prevalence of infection as an index of exposure, and calendar time to predict episodes of malaria on active surveillance malaria data from 2,463 children of under 15 years of age followed for between 5 and 15 years each. Using parameters from the zero-inflated negative binomial model which best fitted our data, we ran 100 simulations of the model based on our population to determine the variation that might be seen due to chance. RESULTS: We identified 212 out of 2,463 children who had a number of clinical episodes above the 95(th) percentile of the simulations run from the model, hereafter referred to as “excess malaria (EM)”. We then identified exposure-matched controls with “average numbers of malaria” episodes, and found that the EM group had higher parasite densities when asymptomatically infected or during clinical malaria, and were less likely to be of haemoglobin AS genotype. CONCLUSIONS: Of the models tested, the negative zero-inflated negative binomial distribution with exposure, calendar year, and age acting as independent predictors, fitted the distribution of clinical malaria the best. Despite accounting for these factors, a group of children suffer excess malaria episodes beyond those predicted by the model. An epidemiological framework for identifying these children will allow us to study factors that may explain excess malaria episodes. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12916-015-0422-4) contains supplementary material, which is available to authorized users

Linking health facility data from young adults aged 18-24 years to longitudinal demographic data: Experience from The Kilifi Health and Demographic Surveillance System

Background: In 2014, a pilot study was conducted to test the feasibility of linking clinic attendance data for young adults at two health facilities to the population register of the Kilifi Health and Demographic Surveillance System (KHDSS). This was part of a cross-sectional survey of health problems of young people, and we tested the feasibility of using the KHDSS platform for the monitoring of future interventions. Methods: Two facilities were used for this study. Clinical data from consenting participants aged 18-24 years were matched to KHDSS records. Data matching was achieved using national identity card numbers or otherwise using a matching algorithm based on names, sex, date of birth, location of residence and the names of other homestead members. A study form was administered to all matched patients to capture reasons for their visits and time taken to access the services. Distance to health facility from a participants’ homestead was also computed. Results: 628 participated in the study: 386 (61%) at Matsangoni Health Centre, and 242 (39%) at Pingilikani Dispensary. 610 (97%) records were matched to the KHDSS register. Most records (605; 96%) were matched within these health facilities, while 5 (1%) were matched during homestead follow-up visits.  463 (75.9%) of those matched were women. Antenatal care (25%), family planning (13%), respiratory infections (9%) and malaria (9%) were the main reasons for seeking care. Antenatal clinic visits (n=175) and malaria (n=27) were the commonest reasons among women and men, respectively. Participants took 1-1.5 hours to access the services; 490 (81.0%) participants lived within 5 kilometres of a facility. Conclusions: With a full-time research clerk at each health facility, linking health-facility attendance data to a longitudinal HDSS platform was feasible and could be used to monitor and evaluate the impact of health interventions on health care outcomes among young people