An investigation into the budding sharing economy in an emerging market

Abstract: In recent times, largely as a result of advancements in information technology and changing consumer needs, traditional methods of doing business are being challenged by the emergence of software platforms that enable individuals to share goods and services at a given cost. Collaborative consumption also referred to as shared economy, entails individuals offering or renting underutilized assets or services to other individuals usually at a specified price. Enabled by the internet, it is now possible for these assets and services to be disaggregated as peer-to-peer services. The collaborative economy has increasingly grown in recent years to become an integral part of modern society where millions of consumers are utilizing it worldwide. It has raked in billions of dollars in revenue worldwide and is expected to grow substantially. Sharing economy companies such as Uber and Airbnb have grown enough to pose a threat to traditional business models. The purpose of this paper is to investigate the shared economy practices as well the concerns it has brought about. In emerging markets the sharing economy for instance seen to have a higher potential in revenue generation though there has been little study conducted. This may prompt further research in investigating the emerging market potential in exploiting the sharing economy in terms of revenue generation while addressing its concerns

PSYCHOSOCIAL IMPACT OF COVID-19 ON STUDENTS AT INSTITUTIONS OF HIGHER LEARNING

Students at higher institutions of learning are more susceptible to psychosocial problems compared to the general public. These may further be exacerbated by the measures put in place to curb the spread of COVID-19. This mixed methods study examined the factors associated with the psychosocial impact of COVID-19 on students’ financial stability, interpersonal relationships and worries related to achieving academic milestones. Data comprised of a series of closed and open-ended questions collected via Qualtrics from students in the United States and Africa (Central and West). The quantitative data were analyzed using frequency counts, percentages and chi-square, while the qualitative data was analyzed using thematic content analysis. More than 90% of the students resided in the United States, 72.5% were females and 78.4% were undergraduates. Financial hardship was experienced by 26.4% of the students, 55.8% indicated that COVID-19 negatively affected their relationship with friends and over 40% worried over delays in achieving academic milestones. Continent of residence, employment status and financial hardship were significantly associated with the negative impact of COVID-19 on one or more of the students’ relationships and with worries about achieving academic milestones. Qualitative data support the findings that financial hardship contributed to experience of psychological distress by students. It also revealed negative (compromised relationships – broken or fractured relationships and loneliness) and positive (bonding) impact of COVID-19 on interpersonal relationships. School administrators should provide students with resources to access economic relief packages and tele-counseling services to help meet their financial and psychosocial support needs amidst COVID-19.  Article visualizations

Risk factors for human brucellosis in northern Tanzania

Little is known about the epidemiology of human brucellosis in sub-Saharan Africa. This hampers prevention and control efforts at the individual and population levels. To evaluate risk factors for brucellosis in northern Tanzania, we conducted a study of patients presenting with fever to two hospitals in Moshi, Tanzania. Serum taken at enrollment and at 4–6 week follow-up was tested by Brucella microagglutination test. Among participants with a clinically compatible illness, confirmed brucellosis cases were defined as having a ≥ 4-fold rise in agglutination titer between paired sera or a blood culture positive for Brucella spp., and probable brucellosis cases were defined as having a single reciprocal titer ≥ 160. Controls had reciprocal titers < 20 in paired sera. We collected demographic and clinical information and administered a risk factor questionnaire. Of 562 participants in the analysis, 50 (8.9%) had confirmed or probable brucellosis. Multivariable analysis showed that risk factors for brucellosis included assisting goat or sheep births (Odds ratio [OR] 5.9, 95% confidence interval [CI] 1.4, 24.6) and having contact with cattle (OR 1.2, 95% CI 1.0, 1.4). Consuming boiled or pasteurized dairy products was protective against brucellosis (OR 0.12, 95% CI 0.02, 0.93). No participants received a clinical diagnosis of brucellosis from their healthcare providers. The under-recognition of brucellosis by healthcare workers could be addressed with clinician education and better access to brucellosis diagnostic tests. Interventions focused on protecting livestock keepers, especially those who assist goat or sheep births, are needed

Risk factors for human acute leptospirosis in northern Tanzania

Introduction: Leptospirosis is a major cause of febrile illness in Africa but little is known about risk factors for human infection. We conducted a cross-sectional study to investigate risk factors for acute leptospirosis and Leptospira seropositivity among patients with fever attending referral hospitals in northern Tanzania. Methods: We enrolled patients with fever from two referral hospitals in Moshi, Tanzania, 2012–2014, and performed Leptospira microscopic agglutination testing on acute and convalescent serum. Cases of acute leptospirosis were participants with a four-fold rise in antibody titers, or a single reciprocal titer ≥800. Seropositive participants required a single titer ≥100, and controls had titers <100 in both acute and convalescent samples. We administered a questionnaire to assess risk behaviors over the preceding 30 days. We created cumulative scales of exposure to livestock urine, rodents, and surface water, and calculated odds ratios (OR) for individual behaviors and for cumulative exposure variables. Results: We identified 24 acute cases, 252 seropositive participants, and 592 controls. Rice farming (OR 14.6), cleaning cattle waste (OR 4.3), feeding cattle (OR 3.9), farm work (OR 3.3), and an increasing cattle urine exposure score (OR 1.2 per point) were associated with acute leptospirosis. Conclusions: In our population, exposure to cattle and rice farming were risk factors for acute leptospirosis. Although further data is needed, these results suggest that cattle may be an important source of human leptospirosis. Further investigation is needed to explore the potential for control of livestock Leptospira infection to reduce human disease

Analysis of Farmers’ Perceptions of the Effects of Climate Change in Kenya: the Case of Kyuso District

A cross-sectional analysis was carried out to evaluate how farmers in Kyuso District have perceived climate change. Data was collected from 246 farmers from six locations sampled out through a multistage and simple random sampling procedure. The logistic regression analysis was carried out to assess factors influencing farmers’ perceptions of climate change. The analysis revealed that 94% of farmers in Kyuso District had a perception that climate was changing.  In this regard, age of the household head, gender, education, farming experience, household size, distance to the nearest input/output market, access to irrigation water, local agro-ecology, access to information on climate change, access to extension services, off farm income and change in temperature and precipitation were found to have significant influence on the probability of farmers to perceive climate change. Since the level of perception to climate change revealed by the study was found to be high (94%), the study suggests that more policy efforts should thus be geared towards helping farmers to adapt to climate change. Key words: Climate change, Perceptions, Logistic regression, Kyuso District

Socio-Economic and Institutional Constraints to Accessing Credit among Smallholder Farmers in Nyandarua District, Kenya

Amongst the challenges faced by smallholder farmers in production is inaccessibility to credit. This study sought to identify household socio-economic and institutional constraints influencing access to credit among smallholder farmers in Nyandarua District. The study used a Logit model. Both quantitative and qualitative data were acquired from primary and secondary sources. Primary data was collected using questionnaires through a survey design. A sample of 164 smallholder farmers was selected using stratified, multi-stage random sampling techniques. Data was analyzed using descriptive statistics and maximum likelihood method using Statistical Package for Social Sciences (SPSS). The study established that socio-economic constraints such as age, gender, household size, farm income, collateral and awareness are critical determinants of access to credit. The study also established that institutional requirements such as costs involved in operating / maintaining bank accounts, loan requirements and transaction costs involved in the credit process influenced access to credit. The study concludes that household socio-economic characteristics and institutional requirements influence access to credit. Key recommendations made include the need by government to deal with bureaucracies involved in land registration to benefit majority of smallholder farmers who remain insecure in the land they use without proof of ownership and also to make easier the registration of lease certificates for those who do not own land and use land on leasehold tenure system. Financial institutions should also put in place less stringent credit requirements and reduce credit costs especially interest rates to make credit more affordable. Keywords: socio-economic and institutional constraints, credit access, smallholder farmers, logit model

Assessment of Farmers’ Adaptation to the Effects of Climate Change in Kenya: the Case of Kyuso District

The study was carried out to assess how farmers in Kyuso District have adapted to the effects of climate change. Survey data was collected from 246 farmers from six locations that were sampled out through a multistage and simple random sampling procedure. The probit regression model was fitted into the data in order to assess factors influencing farmers’ adaptation to the effects of climate change. The analysis revealed that 85% of the farmers had adapted in various ways to the effects of climate change. In this regard, the age of the farmer, gender, education, farming experience, farm income, access to climate information, household size, local agro-ecology, distance to input/output market, access to credit, access to water for irrigation, precipitation and temperature were found to have significant influence on the probability of farmers to adapt to climate change. The study suggests that more policy efforts should thus be geared towards helping all the farmers in the district to adapt to climate change. Key words: climate change, adaptation, probit regression model, Kyuso District

Quantifying social contacts in a household setting of rural Kenya using wearable proximity sensors

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