Changing Perception through a Participatory Approach by Involving Adolescent School Children in Evaluating Smart Food Dishes in School Feeding Programs – Real-Time Experience from Central and Northern Tanzania

The study aimed to test the prospects for, and acceptance of, pigeonpea and finger millet-based dishes in a school feeding program for 2822 adolescents’ in Central Tanzania. The focus was on incorporating nutritious and resilient crops like finger millet and pigeonpea through a participatory approach involving series of theoretical and practical training sessions, for the period of 6 months on the nutritional quality and sensory characteristics of these two unexplored foods in Tanzania. Sharing knowledge on the nutritional value of these crops and involving students in the acceptance study changed their negative perception of finger millet and pigeonpea by 79.5% and 70.3%, respectively. Fifteen months after the study period, schools were still continued feeding the dishes and more than 95% of the students wanted to eat the finger millet and pigeonpea dishes at school. Around 84.2% of the students wanted to include pigeonpea 2–7 times a week and 79.6% of the students wanted to include finger millet on all 7 days in school meal. The study proved that it is possible to change food perceptions and bring about behavior change by sharing knowledge on their benefits and by engaging the consumers through a participatory and culturally appropriate approach

Assessment of Heavy Metals in Rooftop dust around Lake Nakuru Basin, Kenya

Abstract Samples of sedimented dust on roofs from 34 locations within the Lake Nakuru Basin (LNB

Chickpea Genotypes Contrasting for Vigor and Canopy Conductance Also Differ in Their Dependence on Different Water Transport Pathways

Lower plant transpiration rate (TR) under high vapor pressure deficit (VPD) conditions and early plant vigor are proposed as major traits influencing the rate of crop water use and possibly the fitness of chickpea lines to specific terminal drought conditions—this being the major constraint limiting chickpea productivity. The physiological mechanisms underlying difference in TR under high VPD and vigor are still unresolved, and so is the link between vigor and TR. Lower TR is hypothesized to relate to hydraulic conductance differences. Experiments were conducted in both soil (Vertisol) and hydroponic culture. The assessment of the TR response to increasing VPD showed that high vigor genotypes had TR restriction under high VPD, and this was confirmed in the early vigor parent and progeny genotype (ICC 4958 and RIL 211) having lower TR than the late vigor parent and progeny genotype (ICC 1882 and RIL 022). Inhibition of water transport pathways [apoplast and symplast (aquaporins)] in intact plants led to a lower transpiration inhibition in the early vigor/low TR genotypes than in the late vigor/high TR genotypes. De-rooted shoot treatment with an aquaporin inhibitor led to a lower transpiration inhibition in the early vigor/low TR genotypes than in the late vigor/high TR genotypes. Early vigor genotypes had lower root hydraulic conductivity than late vigor/high TR genotypes. Under inhibited conditions (apoplast, symplast), root hydraulic conductivity was reduced more in the late vigor/high TR genotypes than in the early vigor/low TR genotypes. We interpret that early vigor/low TR genotypes have a lower involvement of aquaporins in water transport pathways and may also have a smaller apoplastic pathway than high TR genotypes, which could explain the transpiration restriction under high VPD and would be helpful to conserve soil water under high evaporative demand. These findings open an opportunity for breeding to tailor genotypes with different “dosage” of these traits toward adaptation to varying drought-prone environments

Identifying landscape hot and cold spots of soil greenhouse gas fluxes by combining field measurements and remote sensing data

Upscaling chamber measurements of soil greenhouse gas (GHG) fluxes from point scale to landscape scale remain challenging due to the high variability in the fluxes in space and time. This study measured GHG fluxes and soil parameters at selected point locations (n=268), thereby implementing a stratified sampling approach on a mixed-land-use landscape (∼5.8 km2). Based on these field-based measurements and remotely sensed data on landscape and vegetation properties, we used random forest (RF) models to predict GHG fluxes at a landscape scale (1 m resolution) in summer and autumn. The RF models, combining field-measured soil parameters and remotely sensed data, outperformed those with field-measured predictors or remotely sensed data alone. Available satellite data products from Sentinel-2 on vegetation cover and water content played a more significant role than those attributes derived from a digital elevation model, possibly due to their ability to capture both spatial and seasonal changes in the ecosystem parameters within the landscape. Similar seasonal patterns of higher soil/ecosystem respiration (SR/ER–CO2) and nitrous oxide (N2O) fluxes in summer and higher methane (CH4) uptake in autumn were observed in both the measured and predicted landscape fluxes. Based on the upscaled fluxes, we also assessed the contribution of hot spots to the total landscape fluxes. The identified emission hot spots occupied a small landscape area (7 % to 16 %) but accounted for up to 42 % of the landscape GHG fluxes. Our study showed that combining remotely sensed data with chamber measurements and soil properties is a promising approach for identifying spatial patterns and hot spots of GHG fluxes across heterogeneous landscapes. Such information may be used to inform targeted mitigation strategies at the landscape scale.</p

Seroprevalence of anti-SARS-CoV-2 IgG antibodies in Kenyan blood donors.

The spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in Africa is poorly described. The first case of SARS-CoV-2 in Kenya was reported on 12 March 2020, and an overwhelming number of cases and deaths were expected, but by 31 July 2020, there were only 20,636 cases and 341 deaths. However, the extent of SARS-CoV-2 exposure in the community remains unknown. We determined the prevalence of anti-SARS-CoV-2 immunoglobulin G among blood donors in Kenya in April-June 2020. Crude seroprevalence was 5.6% (174 of 3098). Population-weighted, test-performance-adjusted national seroprevalence was 4.3% (95% confidence interval, 2.9 to 5.8%) and was highest in urban counties Mombasa (8.0%), Nairobi (7.3%), and Kisumu (5.5%). SARS-CoV-2 exposure is more extensive than indicated by case-based surveillance, and these results will help guide the pandemic response in Kenya and across Africa

Revealing the extent of the first wave of the COVID-19 pandemic in Kenya based on serological and PCR-test data.

Policymakers in Africa need robust estimates of the current and future spread of SARS-CoV-2. We used national surveillance PCR test, serological survey and mobility data to develop and fit a county-specific transmission model for Kenya up to the end of September 2020, which encompasses the first wave of SARS-CoV-2 transmission in the country. We estimate that the first wave of the SARS-CoV-2 pandemic peaked before the end of July 2020 in the major urban counties, with 30-50% of residents infected. Our analysis suggests, first, that the reported low COVID-19 disease burden in Kenya cannot be explained solely by limited spread of the virus, and second, that a 30-50% attack rate was not sufficient to avoid a further wave of transmission

Revealing the extent of the first wave of the COVID-19 pandemic in Kenya based on serological and PCR-test data

Policymakers in Africa need robust estimates of the current and future spread of SARS-CoV-2. We used national surveillance PCR test, serological survey and mobility data to develop and fit a county-specific transmission model for Kenya up to the end of September 2020, which encompasses the first wave of SARS-CoV-2 transmission in the country. We estimate that the first wave of the SARS-CoV-2 pandemic peaked before the end of July 2020 in the major urban counties, with 30-50% of residents infected. Our analysis suggests, first, that the reported low COVID-19 disease burden in Kenya cannot be explained solely by limited spread of the virus, and second, that a 30-50% attack rate was not sufficient to avoid a further wave of transmission.</ns4:p

COVID-19 transmission dynamics underlying epidemic waves in Kenya

Policy decisions on COVID-19 interventions should be informed by a local, regional and national understanding of SARS-CoV-2 transmission. Epidemic waves may result when restrictions are lifted or poorly adhered to, variants with new phenotypic properties successfully invade, or when infection spreads to susceptible sub-populations. Three COVID-19 epidemic waves have been observed in Kenya. Using a mechanistic mathematical model, we explain the first two distinct waves by differences in contact rates in high and low social-economic groups, and the third wave by the introduction of higher-transmissibility variants. Reopening schools led to a minor increase in transmission between the second and third waves. Socio-economic and urban/rural population structure are critical determinants of viral transmission in Kenya

SARS-CoV-2 seroprevalence and implications for population immunity: Evidence from two Health and Demographic Surveillance System sites in Kenya, February-December 2022.

BACKGROUND: We sought to estimate SARS-CoV-2 antibody seroprevalence within representative samples of the Kenyan population during the third year of the COVID-19 pandemic and the second year of COVID-19 vaccine use. METHODS: We conducted cross-sectional serosurveys among randomly selected, age-stratified samples of Health and Demographic Surveillance System (HDSS) residents in Kilifi and Nairobi. Anti-spike (anti-S) immunoglobulin G (IgG) serostatus was measured using a validated in-house ELISA and antibody concentrations estimated with reference to the WHO International Standard for anti-SARS-CoV-2 immunoglobulin. RESULTS: HDSS residents were sampled in February-June 2022 (Kilifi HDSS N = 852; Nairobi Urban HDSS N = 851) and in August-December 2022 (N = 850 for both sites). Population-weighted coverage for ≥1 doses of COVID-19 vaccine were 11.1% (9.1-13.2%) among Kilifi HDSS residents by November 2022 and 34.2% (30.7-37.6%) among Nairobi Urban HDSS residents by December 2022. Population-weighted anti-S IgG seroprevalence among Kilifi HDSS residents increased from 69.1% (65.8-72.3%) by May 2022 to 77.4% (74.4-80.2%) by November 2022. Within the Nairobi Urban HDSS, seroprevalence by June 2022 was 88.5% (86.1-90.6%), comparable with seroprevalence by December 2022 (92.2%; 90.2-93.9%). For both surveys, seroprevalence was significantly lower among Kilifi HDSS residents than among Nairobi Urban HDSS residents, as were antibody concentrations (p < 0.001). CONCLUSION: More than 70% of Kilifi residents and 90% of Nairobi residents were seropositive for anti-S IgG by the end of 2022. There is a potential immunity gap in rural Kenya; implementation of interventions to improve COVID-19 vaccine uptake among sub-groups at increased risk of severe COVID-19 in rural settings is recommended