Number of Working Days Lost Due To Diarrhoeal Diseases
English: average number of working days lost due to diarrhoeal diseases in the past 30 days
French: nombre moyen de jours de travail perdus en raison de maladies diarrhéiques au cours des 30 derniers jours
Czech: průměrný počet pracovních dnů ztracených kvůli průjmovým onemocněním během posledních 30 dnů
What is its purpose?
The indicator assesses one of the main socio-economic impacts of diarrhoeal diseases - the inability to work due to feeling unwell or the need to take care of a sick child.
How to Collect and Analyse the Required Data
Collect the following data by conducting individual interviews with a representative sample of your target group members:
RECOMMENDED SURVEY QUESTIONS (Q) AND POSSIBLE ANSWERS (A)
Q1: In the past 30 days, was there any day when you or another family member could not work (on the farm, in business ...) because of having diarrhoea?
A1: yes / no / does not remember
(ask the next questions only if the previous answers is YES)
Q2: For how many days could you/ another family member not work?
A2: .... days
Q3: In the past 30 days, was there any day when you or another family member could not work because you had to take care of a child with diarrhoea?
A3: yes / no / does not remember
(ask the next question only if the previous answers is YES)
Q4: For how many days could you/ another family member not work?
A4: .... days
Calculate the indicator's value by summing up the number of working days lost due to diarrhea and dividing it by the total number of respondents (exclude those whose answer was "does not remember").
1) The longer the recall period you use, the more "days lost" you will record; however, the accuracy of such responses will be low (as people simply do not remember exactly). On the other hand, short recall periods will give you more accurate responses; however, in order to generate a representative sample, you will need to interview a very large number of respondents. The proposed 30 days recall period is a trade-off between these two options, reflecting the realistic possibilities of the project surveys while aiming for sufficient accuracy.
2) Disaggregate the data by wealth.