This study examined the effect of sales force turnover on the corporate image of selected organizations in Anambra State. The general objective of the study is to ascertain the effect of sales force turnover on corporate image of marketing organizations in Anambra State. The research adopted a survey design which made use of primary source data for analysis. The population of the study consists of 268 sales force personnel and 246 customers of selected marketing organizations. Based on the determined sample size of 514, copies of the questionnaire were distributed to respondents: 268 to companies' sales staff, 246 to companies' customers. Out of the total number of 268 copies of questionnaire distributed to staff, only 260 copies were returned well completed and fit for use in analyses. Out of this 246, 240 were well completed and used for analyses. The instrument of data collection consists of two sets of Likert-type, five-point scale self-administered questionnaire for staff and customers of selected marketing organizations of the study. The Pearson chi-square tests were used to test the five hypotheses of the study. The findings of the study showed that high sales force turnover has significant effect on the corporate image of marketing organizations in Anambra State; voluntary sales force turnover has significant effect on corporate image of marketing organizations in Anambra State. The findings of the study further revealed that long time retention of sales force has significant effect on the corporate image of marketing organization in Anambra State, and that customers' impressions of the sales force have significant effect on the corporate image of marketing organizations in Anambra State. Based on the findings of the study, it is recommended that marketing organizations in Anambra State should: invest more in the general welfare of their sales force to ensure employees stability and to work hard to keep the rate of voluntary sales force turnover to the barest minimum among others.

Fruits and vegetables have numerous health importance but can act as vehicles in the transmission of foodborne diseases of public health importance. This research examined the presence of parasites and microbial organisms on fruits sold at Otuoke community, Ogbia Local Government Area, Bayelsa State, Nigeria using six fruits types, including pineapple (Ananas comosus), cucumber (Cucumis sativus), lime (Citrus aurantiifolia), garden egg (Solanum aethiopicum), guava (Psidium guajava) and orange (Citrus sinensis). The parasites were concentrated by sedimentation and were examined using a light microscope. The result of the study showed the presence of cysts of Cryptosporidium parvum, Entamoeba histolytica, eggs of Fasciola hepatica, Ascaris lumbricoides and larva of Strongyloides stercoralis. Five out of the 6 fruits types examined were infested with at least one type of parasites. Ascaris lumbricoides (33.33%) was the most frequently detected parasite and was found on the pineapple, guava and oranges fruits. Fruit types were not significantly associated with parasitic contamination (p > 0.005). Bacteria isolated from the fruits included Lactobacillus sp., Proteus mirabilis, Bacillus subtilis, Pseudomonas sp., Bacillus cereus, Salmonella typhi, Shigella sp., Escherichia coli and Staphylococcus aureus. E. coli was isolated in all the sampled fruits types. The total count was determined by pour plate method using MacConkey agar. Total viable bacteria count (TBC) ranged from 21.9 x 105cfu/ml to 7.27 x 105cfu/ml. Aspergillus niger, A. flavus, Mucor spp.. and Fusarium spp were the isolated fungi species. A high number of these microorganisms in fruits and vegetables can lead to public health emergencies. Risk reduction can be achieved through personal and food hygiene by the fruit sellers and consumers. Further studies should be conducted to address the effect of seasonal variation on the infestation of the fruits sold in this area.

Background: This study aims to investigate the relationship between meteorological parameters and malaria epidemiology to identify an optimal model for predicting and understanding the spread of malaria in Rivers State of Nigeria. Malaria remains a significant public health concern, particularly in tropical and subtropical regions, where climatic factors play a crucial role in its transmission dynamics. By analyzing historical malaria and meteorological data from Rivers State, we developed a comprehensive modeling framework to quantify the impact of meteorological parameters on malaria incidence. Method: Five statistical models for count data were employed to identify the most influential meteorological variables and establish their associations with malaria transmission. Results: The results obtained show that, the best count data model out of the five models considered in this study is the Quasi-Poisson Regression Model because it resulted to smaller Mean Absolute Percentage Error (MAPE) and Root Mean Square Error (RMSE) values. The Quasi-Poisson Regression Model showed that none of the meteorological variables used in the models were significant at 5% level of significance in predicting the number of cases of malaria in the study location. Conclusion: The findings of this study highlight the need for a multifaceted approach to malaria control in Rivers State, addressing not only the meteorological factors but also the biological, social and economic determinants of the disease. The identified optimal model serves as a valuable resource for policymakers, researchers, and healthcare practitioners, enabling them to make informed decisions and implement targeted interventions to mitigate the impact of malaria outbreaks.

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