Responses and Impacts of COVID-19 on East Africa’s Tourism Industry

The COVID-19 pandemic has affected all economies and life support systems world-wide. Owing to the pandemic's unpredictable nature, experts and policymakers struggle to find a headway to slow infections and further economic deterioration. The purpose of this study is to assess East African Community (EAC) states’ early responses and the pandemic’s impacts on the tourism industry. Data were collected through a review of secondary data, including academic and media reports. Special attention was paid to respective policy responses during the early stages of the pandemic outbreak. Findings show that Kenya, Uganda, and Rwanda employed more robust measures to curb the spread of COVID-19, whereas Tanzania and Burundi resorted to censorship and protectionism. The EAC should quickly learn from the current crisis and devise strategies to handle future shocks to the tourism-system. The states should prioritize economic diversification, retraining of the workforce, global engagement, and collaborative management.

Accuracy, Precision, And Agreement Statistical Tests For Bland-Altman Method

Background: Bland and Altman plot method is a widely cited graphical approach to assess equivalence of quantitative measurement techniques. Perhaps due to its graphical output, it has been widely applied, however often misinterpreted by lacking of inferential statistical support. To compare data sets obtained from two measurement techniques, researchers may apply Pearson’s correlation, ordinal least-square linear regression, or the Bland-Altman plot methods, failing to locate the weakness of each measurement technique. We aim to develop and distribute a statistical method in R in order to add robust and suitable inferential statistics of equivalence. Methods: Three nested tests based on structural regressions are proposed to assess the equivalence of structural means (accuracy), equivalence of structural variances (precision), and concordance with the structural bisector line (agreement in measurements of data pairs obtained from the same subject) to reach statistical support for the equivalence of measurement techniques. Graphical outputs illustrating these three tests were added to follow Bland and Altman’s principles of easy communication. Results: Statistical p-values and robust approach by bootstrapping with corresponding graphs provide objective, robust measures of equivalence. Five pairs of data sets were analyzed in order to criticize previously published articles that applied the Bland and Altman’s principles, thus showing the suitability of the present statistical approach. In one case it was demonstrated strict equivalence, three cases showed partial equivalence, and one case showed poor equivalence. Package containing open codes and data is available with installation instructions on SourceForge for free distribution. Conclusions: Statistical p-values and robust approach assess the equivalence of accuracy, precision, and agreement for measurement techniques. Decomposition in three tests helps the location of any disagreement as a means to fix a new technique.

Impact of Vision and Hearing Impairment on Cognition and Loneliness: Evidence From the Mexican Health and Aging Study

Poor vision and hearing have been associated with lower cognitive function and greater social isolation (i.e., loneliness) among older adults. However, this evidence is based largely on data from non-Hispanic populations. Therefore, we investigated whether self-reported vision and hearing was associated with cognitive function and loneliness in a nationally-representative study of Mexican adults aged 50 and older in Wave 3 of the Mexican Health and Aging Study. The final sample included 12,426 participants. The majority were female (58%), and the mean age was 67. Self-reported vision and hearing status were categorized as excellent-very good [ref], good, and fair-poor. Measures for global cognition, memory, and non-memory cognition were calculated using z-scores based on nine cognitive tests. Participants who reported frequently feeling a lack of companionship, left out, or isolated were categorized as feeling lonely. All analyses controlled for age, sex, and years of education. Participants with fair-poor vision had lower global (β= -0.06, p <.01), memory (β= -0.07, p <.01), and non-memory cognition (β= -0.06, p <.01) than participants with excellent-very good vision. In addition, participants with fair-poor hearing had higher non-memory cognition (β= 0.03, p <.05) but not global cognition (β=0.02) or memory (β=0.001). Fair-poor vision (OR=1.53, 95% CI=1.25-1.87) but not fair-poor hearing (OR=1.16, 95% CI=0.97-1.38) was associated with higher odds of being lonely. Poor vision may be a potentially modifiable risk factor for lower cognition and loneliness among Mexican adults. Future research should incorporate robust measures of sensory health and investigate the longitudinal association between vision, cognition, and loneliness.

A continuous indicator of food environment nutritional quality

Food environments can profoundly impact diet and related diseases. Effective, robust measures of food environment nutritional quality are required by researchers and policymakers investigating their effects on individual dietary behavior and designing targeted public health interventions. The most commonly used indicators of food environment nutritional quality are limited to measuring the binary presence or absence of entire categories of food outlet type, such as 'fast-food' outlets, which can range from burger joints to salad chains. This work introduces a summarizing indicator of restaurant nutritional quality that exists along a continuum, and which can be applied at scale to make distinctions between diverse restaurants within and across categories of food outlets. Verified nutrient data for a set of over 500 chain restaurants is used as ground-truth data to validate the approach. We illustrate the use of the validated indicator to characterize food environments at the scale of an entire jurisdiction, demonstrating how making distinctions between different shades of nutritiousness can help to uncover hidden patterns of disparities in access to high nutritional quality food.

Validation of the General and Personal Belief in a Just World scales in Iran and Their Relations to Perceived Threat of Kin Favoritism

People possess a pre-conscious need to believe in the existence of justice in the world. This belief in a just world (BJW) is usually measured with self-report scales. Dalbert et al. (1987) and Dalbert (1999) have developed the general belief in a just world (GBJW) and personal belief in a just world (PBJW) scales as psychometrically robust measures of just-world beliefs. We conducted three studies to demonstrate the validity of the Persian versions of belief in a just world scales and the importance of distinguishing between GBJW and PBJW. First, we confirmed the factor structure. reliability, convergent validity (self-esteem, life satisfaction, and religiosity), and divergent validity (big five personalityfactors and dark triad traits) of GBJW and PBJW using Iranian participants (N1 = 454). Second, the associations of GBJW and PBJW with perceived threat of unjust behavior directed to self or others were assessed using two scenario-based studies (N2 = 81, N3 = 71) in the context of kin favoritism. While GBJW negatively predicted perceived threat of kin favoritism directed to others, PBJW was a negative predictor of perceived threat of kin favoritism directed to self. Consistent with theoretical assumptions, perceived likelihood of punishment mediated these associations. In addition to providing further evidence for the differentiation between GBJW and PBJW, the findings of Study 2 and 3 also support the idea of an optimistic bias towards self by showing that people perceived less threat of kin favoritism when others, rather than themselves, were potential victims of injustice.

Niche diversity influences psychometric properties of a brief personality scale – evidence from representative samples during the COVID-19 pandemic

Recent studies using more diverse samples have questioned the applicability of the Big Five. It needs to be shown how robust measures of the big five are and whether any deviations are systematic or random. We present validity information on a ten-item personality measure applied to population samples in 16 nations during the first wave of the COVID-19 pandemic (N=35,052). Overall, we found poor replicability and low reliability of the five-factor structure of personality. We then test whether variation is systematically related to ecological, economic or stress-related variables. Personality structure replicability measured via averaged Tucker’s Φ values was correlated with niche diversity data (Human development index, rate of urbanization, diversity of export goods) and national wealth, but not reliably related with COVID-19 (gross domestic product per capita). and death rates per million citizens during the study period. These patterns overall suggest that a) personality structure in brief measures need to be carefully tested prior to any substantive interpretations of the personality data and b) that systematic socioecological factors have an impact on survey responses to personality inventories.

Exponential-Ratio-Type Imputation Class of Estimators using Nonconventional Robust Measures of Dispersions

Human-assisted surveys, such as medical and social science surveys, are frequently plagued by non-response or missing observations. Several authors have devised different imputation algorithms to account for missing observations during analyses. Nonetheless, several of these imputation schemes' estimators are based on known auxiliary variable parameters that can be influenced by outliers. In this paper, we suggested new classes of exponential-ratio-type imputation method that uses parameters that are robust against outliers. Using the Taylor series expansion technique, the MSE of the class of estimators presented was derived up to first order approximation. Conditions were also specified for which the new estimators were more efficient than the other estimators studied in the study. The results of numerical examples through simulations revealed that the suggested class of estimators is more efficient.

Does the inverse farm size productivity hypothesis hold for perennial monocrop systems in developing countries? Evidence from Kenya

The inverse farm size and productivity relationship (IR) is a recurring theme in the literature. However, most previous studies were undertaken within a setting of mixed cropping systems. In this article, we investigate the effect of farm size on productivity within the context of a perennial monocropping system, acute competition for farmland, frequent subdivision of farms and declining yields. We apply household survey data of smallholder tea farms in western Kenya and consider both technical efficiency (TE) and the yield per hectare as indicators of productivity. The findings show that the effect of farm size on productivity is nonlinear, with TE initially declining and then rising with farm size. The findings also demonstrate that the farm size and productivity relationship is important for perennial monocrops and that the use of robust measures of productivity is important for the IR. The findings have important implications for agricultural policy in developing countries.

Estimation of Population Median under Robust Measures of an Auxiliary Variable

In this paper, a generalized class of estimators for the estimation of population median are proposed under simple random sampling without replacement (SRSWOR) through robust measures of the auxiliary variable. Three robust measures, decile mean, Hodges–Lehmann estimator, and trimean of an auxiliary variable, are used. Mathematical properties of the proposed estimators such as bias, mean squared error (MSE), and minimum MSE are derived up to first order of approximation. We considered various real-life datasets and a simulation study to check the potentiality of the proposed estimators over the competitors. Robustness is also examined through a real dataset. Based on the fascinating results, the researchers are encouraged to use the proposed estimators for population median under SRSWOR.