Socioeconomic Factors that Influence Smallholder Farmers’ Membership in a Dairy Cooperative Society in Embu County, Kenya

Smallholder dairy farmers produce the bulk of total marketed milk in Kenya. Dairy cooperatives are one of the avenues for these smallholder farmers to harness markets for their milk. The paper sought to find out the socioeconomic factors that would influence these farmers to join dairy cooperatives in Embu County, Kenya. Systematic random sampling and simple random sampling were used to select a total of 236 smallholder farmers. The data was analysed using descriptive statistics and the binomial logit model. The results show that age, gender, household size, herd size, distance to the nearest market, access to credit and milk sold influenced the decision to join cooperative societies. The study recommends further study whether cooperatives are improving the incomes of smallholder farmers. Keywords:Dairy cooperative society, smallholder farmers, Binomial logit mode

Influence of Social Capital on Producer Groups’ Performance and Market Access Amongst Smallholder French beans Farmers in Kirinyaga County, Kenya

Market access is a major constraint facing agricultural commercialization in Kenya. The pressure on arable land and market changes are mainly felt by the smallholder farmers who are faced with high transaction costs. In addition, these farmers face a number of institutional and technical factors putting their market survival at stake. To curb these challenges, formation of farmer groups and organizations has become important in bringing about collective action whose basis is social capital. However, this capital must be mobilized through group membership and other social dimensions to achieve collective action. This paper therefore, sought determine influence of the social capital dimensions, socio-economic and institutional factors on group’s performance. The study was conducted in Mwea sub-county, Kirinyaga County and a multistage sampling method was used to obtain a sample of 174 farmers (95 group members and 79 non-group members) who were interviewed using structured questionnaires. Descriptive statistics was utilized in characterizing socio-economic attributes of the smallholder French beans farmers. Tobit model was used to determine influence of the social capital dimensions and institutional factors on group’s performance. The results showed that gender, age, education level, French beans yield, farming experience, transport cost, off-farm income, initial social capital endowment, trust index and meeting attendance significantly influenced the extent of commercialization. The results of this study enhanced a better understanding of social capital dimensions in farmer group performance. Key words: Social capital, commercialization, Tobit model, French bean

Determinants of Market Participation among Small-Scale Pineapple Farmers in Kericho County, Kenya

Pineapple (Ananas comosus) is one of the major cash crops grown in Kericho County, Kenya specifically Bureti district. In the study area, pineapples have been perceived to have high market value, resulting in tradeoffs with staple food. Despite pineapples market value, its market participation has not been studied and quantified. Therefore, this paper aims to determine the factors influencing market participation and its extent. A simple random sampling approach was used to select a sample of 150 small-scale pineapple farmers and primary data was collected using a semi-structured questionnaires. The data was analyzed using the descriptive statistics and Heckman two-stage model. The results showed that age, gender, education level and pineapple yields significantly influenced the decision to participate in pineapple marketing. Further, gender, price information, group marketing, marketing experience, vehicle ownership and marketing under contract significantly influenced the extent of market participation. Based on the findings policy implication was drawn for improving the household income in the study area. Key words: Heckman two-stage model, market participation, small-scale pineapple farmers

The evolving SARS-CoV-2 epidemic in Africa: Insights from rapidly expanding genomic surveillance

INTRODUCTION Investment in Africa over the past year with regard to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) sequencing has led to a massive increase in the number of sequences, which, to date, exceeds 100,000 sequences generated to track the pandemic on the continent. These sequences have profoundly affected how public health officials in Africa have navigated the COVID-19 pandemic. RATIONALE We demonstrate how the first 100,000 SARS-CoV-2 sequences from Africa have helped monitor the epidemic on the continent, how genomic surveillance expanded over the course of the pandemic, and how we adapted our sequencing methods to deal with an evolving virus. Finally, we also examine how viral lineages have spread across the continent in a phylogeographic framework to gain insights into the underlying temporal and spatial transmission dynamics for several variants of concern (VOCs). RESULTS Our results indicate that the number of countries in Africa that can sequence the virus within their own borders is growing and that this is coupled with a shorter turnaround time from the time of sampling to sequence submission. Ongoing evolution necessitated the continual updating of primer sets, and, as a result, eight primer sets were designed in tandem with viral evolution and used to ensure effective sequencing of the virus. The pandemic unfolded through multiple waves of infection that were each driven by distinct genetic lineages, with B.1-like ancestral strains associated with the first pandemic wave of infections in 2020. Successive waves on the continent were fueled by different VOCs, with Alpha and Beta cocirculating in distinct spatial patterns during the second wave and Delta and Omicron affecting the whole continent during the third and fourth waves, respectively. Phylogeographic reconstruction points toward distinct differences in viral importation and exportation patterns associated with the Alpha, Beta, Delta, and Omicron variants and subvariants, when considering both Africa versus the rest of the world and viral dissemination within the continent. Our epidemiological and phylogenetic inferences therefore underscore the heterogeneous nature of the pandemic on the continent and highlight key insights and challenges, for instance, recognizing the limitations of low testing proportions. We also highlight the early warning capacity that genomic surveillance in Africa has had for the rest of the world with the detection of new lineages and variants, the most recent being the characterization of various Omicron subvariants. CONCLUSION Sustained investment for diagnostics and genomic surveillance in Africa is needed as the virus continues to evolve. This is important not only to help combat SARS-CoV-2 on the continent but also because it can be used as a platform to help address the many emerging and reemerging infectious disease threats in Africa. In particular, capacity building for local sequencing within countries or within the continent should be prioritized because this is generally associated with shorter turnaround times, providing the most benefit to local public health authorities tasked with pandemic response and mitigation and allowing for the fastest reaction to localized outbreaks. These investments are crucial for pandemic preparedness and response and will serve the health of the continent well into the 21st century

Beyond Endemic Burkitt Lymphoma: Navigating Challenges of Differentiating Childhood Lymphoma Diagnoses Amid Limitations in Pathology Resources in Lilongwe, Malawi

Background. Although Burkitt lymphoma (BL) is the most common childhood lymphoma in sub-Saharan Africa, Hodgkin lymphoma (HL) and other non-Hodgkin lymphomas occur. Diagnosing non-jaw mass presentations is challenging with limited pathology resources. Procedure. We retrospectively analyzed 114 pediatric lymphomas in Lilongwe, Malawi, from December 2011 to June 2013 and compared clinical versus pathology-based diagnoses over two time periods. Access to pathology resources became more consistent in 2013 compared with 2011-2012; pathology interpretations were based on morphology only. Results. Median age was 8.4 years (2.1-16.3). The most common anatomical sites of presentation were palpable abdominal mass 51%, peripheral lymphadenopathy 35%, and jaw mass 34%. There were 51% jaw masses among clinical diagnoses versus 11% in the pathology-based group ( P < .01), whereas 62% of pathology diagnoses involved peripheral lymphadenopathy versus 16% in the clinical group ( P < .01). The breakdown of clinical diagnoses included BL 85%, lymphoblastic lymphoma (LBL) 9%, HL 4%, and diffuse large B-cell lymphoma (DLBCL) 1%, whereas pathology-based diagnoses included HL 38%, BL 36%, LBL 15%, and DLBCL 11% ( P < .01). Lymphoma diagnosis was pathology confirmed in 19/66 patients (29%) in 2011-2012 and 28/48 (60%) in 2013 ( P < .01). The percentage of non-BL diagnoses was consistent across time periods (35%); however, 14/23 (61%) non-BL diagnoses were pathology confirmed in 2011-2012 versus 16/17 (94%) in 2013. Conclusions. Lymphomas other than Burkitt accounted for 35% of childhood lymphoma diagnoses. Over-reliance on clinical diagnosis for BL was a limitation, but confidence in non-BL diagnoses improved with time as pathology confirmation became standard. Increased awareness of non-BL lymphomas in equatorial Africa is warranted