ABSTRACT
The New Zealand health system is data-rich, information-poor, and intelligence meagre. However, there is widespread confusion about the definitions of these terms, so they are often used synonymously. Like many jurisdictions, we continue to collect and collate vast quantities of data at an increasing rate. Many tools are available to "analyse" the data deluge with the false expectation that "intelligence" will be produced. Naively, such a data-driven, machine-analysed paradigm is often thought to produce the "evidence" for decision-making and policy development. Continuing such a blinded approach poses potential health risks to New Zealanders and remains a major impediment to improving our health statusCreating intelligence from information involves humans (perhaps in concert with AI) utilising their interpretative abilities, asking the "so what, "what does it mean" questions, and employing their communication skills to disseminate the answers. To move from information to intelligence requires agencies to employ, develop and maintain a sufficiently skilled workforce over a long period, rather than the quick and easy investment in more and faster machines and software.Only through a human-driven evaluation of intelligence-based decisions and policies will our knowledge about the environmental health system increase and ultimately yield better health outcomes.Environmental Health Intelligence NZ (EHINZ) provides intelligence as evidence for decision-making and policy development in environmental health. It is based on the interpretation, communication, and dissemination of information from the surveillance more than seventy environmental health indicators (EHIs) across twelve domains (e.g., air and water quality, climate change), exposure to hazardous substances, and social vulnerability indicators to environmental hazards (e.g., flooding, climate change, sea-level rise, wildfires, heat waves).The paper details our approach, with two case studies, in providing the NZ health system with "intelligence for environmental health decisions."
ABSTRACT
Social vulnerability indicators are a valuable tool for understanding which population groups are more vulnerable to experiencing negative impacts from disasters, and where these groups live, to inform disaster risk management activities. While many approaches have been used to measure social vulnerability to natural hazards, there is no single method or universally agreed approach. This paper proposes a novel approach to developing social vulnerability indicators, using the example of flooding in Aotearoa New Zealand. A conceptual framework was developed to guide selection of the social vulnerability indicators, based on previous frameworks (including the MOVE framework), consideration of climate change, and a holistic view of health and wellbeing. Using this framework, ten dimensions relating to social vulnerability were identified: exposure; children; older adults; health and disability status; money to cope with crises/losses; social connectedness; knowledge, skills and awareness of natural hazards; safe, secure and healthy housing; food and water to cope with shortage; and decision making and participation. For each dimension, key indicators were identified and implemented, mostly using national Census population data. After development, the indicators were assessed by end users using a case study of Porirua City, New Zealand, then implemented for the whole of New Zealand. These indicators will provide useful data about social vulnerability to floods in New Zealand, and these methods could potentially be adapted for other jurisdictions and other natural hazards, including those relating to climate change.