4 research outputs found
The Effect of Behavioral Factors on Investment Decisions in Real Estate Sector in Nairobi County
Purpose-This study was intent on establishing the effect of behavioral factors on investment decisions in the real estate sector in Nairobi County. The behavioral factors explored for this study were herd behavior, representativeness, anchoring and overconfidence. Methodology-The study exploited descriptive research design to explicate how investors in real estate sector in Nairobi County make investment decisions from a behavioral finance point of view. Descriptive statistics and inferential statistics were used to scrutinize the data. Descriptive statistics adopted in this study included frequencies, mean, percentages and standard deviation. Additionally, inferential statistics of regression models and correlation analysis were used to examine the relationship of the study variables. The scrutinized data were presented in form of frequency tables and pie charts. Findings-The results of the study revealed that 53.71% of the respondents make use of the intuitions when evaluating investment decisions. The outcomes of the study further showed that representativeness, herd behaviour, anchoring and overconfidence have positive correlation coefficients of 0.21, 0.31, 0.16 and 0.32 respectively with the investment decisions in the real estate sector. The multiple R for the regression was 0.817, suggesting a strong positive correlation between the values that the model predicts and the actual values of the dependent variable. The R Square was 0.667 suggesting that about 66.7% of the variation in the real estate investment can be explained by the variation in the extent to which they are influenced by the behavioral factors. The Multiple R and the R Square suggest that behavioral factors exert influence on the investment decisions in the real estate sector. Implications- Behavioural factors analysis provides explanations on the trend of the investors in making critical investment decisions which portray a particular pattern of behaviour in the investment. Investors lack rationality when making decisions about their investments but rather make decisions based on emotions, feelings, mood and sentiments. Value- The study findings will enable investors to acquire skills necessary in eliminating various behavioral biases and increasing their rationality when making investment decisions in the real estate sector
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Exploring Estimates and Reasons for Lost to Follow-Up Among People Living With HIV on Antiretroviral Therapy in Kisumu County, Kenya
BackgroundA better understanding why people living with HIV (PLHIV) become lost to follow-up (LTFU) and determining who is LTFU in a program setting is needed to attain HIV epidemic control.SettingThis retrospective cross-sectional study used an evidence-sampling approach to select health facilities and LTFU patients from a large HIV program supporting 61 health facilities in Kisumu County, Kenya.MethodsEligible PLHIV included adults 18 years and older with at least 1 clinic visit between September 1, 2016, and August 31, 2018, and were LTFU (no clinical contact for ≥90 days after their last expected clinic visit). From March to June 2019, demographic and clinical variables were collected from a sample of LTFU patient files at 12 health facilities. Patient care status and retention outcomes were determined through program tracing.ResultsOf 787 LTFU patients selected and traced, 36% were male, median age was 30.5 years (interquartile range: 24.6-38.0), and 78% had their vital status confirmed with 560 (92%) alive and 52 (8%) deceased. Among 499 (89.0%) with a retention outcome, 233 (46.7%) had stopped care while 266 (53.3%) had self-transferred to another facility. Among those who had stopped care, psychosocial reasons were most common {65.2% [95% confidence interval (CI): 58.9 to 71.1]} followed by structural reasons [29.6% (95% CI: 24.1 to 35.8)] and clinic-based reasons [3.0% (95% CI: 1.4 to 6.2)].ConclusionWe found that more than half of patients LTFU were receiving HIV care elsewhere, leading to a higher overall patient retention rate than routinely reported. Similar strategies could be considered to improve the accuracy of reporting retention in HIV care
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First cases of SARS-CoV-2 infection and secondary transmission in Kisumu, Kenya
We investigated the first 152 laboratory-confirmed SARS-CoV-2 cases (125 primary and 27 secondary) and their 248 close contacts in Kisumu County, Kenya. Conducted June 10-October 8, 2020, this study included interviews and sample collection at enrolment and 14-21 days later. Median age was 35 years (IQR 28-44); 69.0% reported COVID-19 related symptoms, most commonly cough (60.0%), headache (55.2%), fever (53.3%) and loss of taste or smell (43.8%). One in five were hospitalized, 34.4% >25 years of age had at least one comorbidity, and all deaths had comorbidities. Adults ≥25 years with a comorbidity were 3.15 (95% CI 1.37-7.26) times more likely to have been hospitalized or died than participants without a comorbidity. Infectious comorbidities included HIV, tuberculosis, and malaria, but no current cases of influenza, respiratory syncytial virus, dengue fever, leptospirosis or chikungunya were identified. Thirteen (10.4%) of the 125 primary infections transmitted COVID-19 to 27 close contacts, 158 (63.7%) of whom resided or worked within the same household. Thirty-one percent (4 of 13) of those who transmitted COVID-19 to secondary cases were health care workers; no known secondary transmissions occurred between health care workers. This rapid assessment early in the course of the COVID-19 pandemic identified some context-specific characteristics which conflicted with the national line-listing of cases, and which have been substantiated in the year since. These included over two-thirds of cases reporting the development of symptoms during the two weeks after diagnosis, compared to the 7% of cases reported nationally; over half of cases reporting headaches, and nearly half of all cases reporting loss of taste and smell, none of which were reported at the time by the World Health Organization to be common symptoms. This study highlights the importance of rapid in-depth assessments of outbreaks in understanding the local epidemiology and response measures required