Why is there such variation in many of the findings
From Abstract in our work:
Design: Cross-sectional study in Assosa district from November 2011 to March 2012? Overall prevalence was 22.6%. We found T. congolense (58.6%), followed by T. vivax (17.2%), T. brucei (10.3%), T. congolense and T. vivax (10.3%),T.congolense and T. brucei (2.3%) and mixed infection of the three species (1.1%) respectively. Prevalence was higher in older age groups when compared to other age groups? No statistically significant 2 association between the two sexes was found (x = 0.817)?
http://idosi.org/ajad/ajad2%283%292013.htm
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Of course you can to see the change in incidence manner with time and type of patients and environmental impact when changed due to various conditions.
If you are looking at p-values, note that a p-value is a function of sample size and needs a power analysis or other sensitivity analysis, not an arbitrarily set 'level.' (Please see link below.) When applicable, it is generally more useful to examine confidence intervals. Does this relate to your problem?
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Dear Ayalew, It would have been very nice if you have presented confidence intervals for your prevalence estimates of the risk factors you considered. In trypanosomosis the places you two take samples from could vary and the proximity to riverine environment could also vary which can bring about different prevalences over relatively short distances if the altitude of the places change dramatically. However, as far as I am concerned if both studies presented their confidence intervals, the differences could be insignificant (22.2 Vs 28%), (58% Vs 66% for T. congo.) could have an overlapping confidence intervals.
Thank you all colligues..... Many of remarks indicated above had helped me have some insight why some differences hapened
Dr Birhanu, thanks for thw inpur but.... I dont have the raw data now as it was a DVM extern stud work 3 years back....... But I had the glimpse of imagning the scwnarios. THANK you.
The subject discussed does not concern my field. I deal with cause-effec relationships
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