Key Socio-economic Data to Be Collected
Key socio-economic data to be collected in the survey are summarized below for quick reference:
- Population (e.g. size, characteristics and distribution);
- Household characteristics (e.g. size, female-headed, age, sex and decision-making structure, etc.);
- Use, availability and loss/gain of resources (e.g. productive agricultural and commercial/industrial and residential lands and their values to the economy);
- Household income (sources, size/amount by sex, earners, etc.);
- Job opportunities and employment structure and patterns (lost income opportunities or loss of income sources due to POPs/chemical pollution, loss of food sources (fish, poultry, livestock, animal husbandry, etc.);
- Local economic system and structure;
- Local food supplies, livelihoods, organizations/institutions; and
- Other infrastructure such as roads, water supply, schools, pagoda / temple / mosque / church, etc.
The coverage should include residences or places of work located within a 1-2 km radius of the suspected Hot Spot. Sites further afield can also be selected if they are likely influenced by contaminants.
Sampling Design and Field Data Collection
Both random and non-random sampling should be considered. Sampling bias can be avoided through the use of random or stratified random sampling techniques. However, during screening studies, targeted (i.e. non-random) sampling should be considered in order to assess worst-case examples.
The pre-survey activities should include:
- Review of existing site information (e.g., Government statistics, other survey results, etc.);
- Meetings with district/city/town/commune/village authorities;
- Discussions with key informants (e.g. villagers, local leaders, elders, etc.); and
- Field observations.
Households to be interviewed will be selected based on pre-survey work, and availability/interest of target populations. Close coordination with local health authorities is usually necessary, and government policies on the release of data release should be clarified in advance of data collection.