4 1 2 Defining the current situation - epidemiology 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 Paul R Hunter, Helen Risebro INTRODUCTION The first step in any economic appraisal or evaluation is to understand the underlying problem being addressed (see Chapter 1). Clearly such analysis of drinking-water interventions will have a strong public health element. This chapter introduces the reader to the role that epidemiology has in determining the burden of disease in a community that may be attributable to lack of access to safe drinking-water and/or adequate sanitation. In order to determine how important such an issue may be one has to ask three questions: What is the burden of disease in the target group? Burden of disease is a function of the incidence and severity of the disease. What proportion of the burden of disease is due to deficiencies in access to drinking-water to be remedied by the intervention? Are there any spin-off livelihood responses that would result from the outcomes of the intervention? 1 WHO Guide to Understanding Costs and Benefits of Water Interventions In Press, World Health Organization, Geneva. http://www.who.int/water_sanitation_health/economic/chapter4.pdf19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 This chapter primarily concerns itself with answering the first two questions. Specific data challenges related to livelihood analysis will be raised in the next chapter. The rest of this chapter is primarily concerned with assisting decision makers in gathering evidence to enable them to make an informed decision whether or not there is a public health need for an intervention, as a prerequisite to undertaking a full economic assessment. The chapter introduces the reader to some of the methods of epidemiology to better understand epidemiological papers and reports. The chapter then goes on to describe how existing analyses may be used to estimate disease burden MEASURES OF DISEASE OCCURRENCE The two predominant measures of disease occurrence are prevalence and incidence. Prevalence Prevalence measures the amount of disease in a population at a given time point and can be expressed as a percentage or shown as cases/population: 37 38 39 40 41 42 43 44 45 46 47 48 Number of existing cases in defined population at a given point in time Number of people in the defined population at the same point in time The point prevalence is a single assessment of a fixed point in time whereas the period prevalence is the percentage of a population that are cases at any time within a stated period. Period prevalence is preferred in infectious disease epidemiology as it can be used when there are repeated or continual assessments of the same individuals over a period of time (such as, multiple episodes of diarrhoea). Longitudinal prevalence can be calculated using the following formula (Morris, 1996): 49 50 51 52 53 54 Number of days with diarrhoea Number of days under observation Incidence Incidence measures the number of new cases of disease in a population over a specific time period. When the population is constant the incidence risk is measured as: 255 56 57 58 59 60 61 62 Number of people who develop disease over a defined period of time Number of disease-free people in that population at the start of the time period When the population is not constant, for example, through deaths, migration, births, or through additional participant recruitment, the incidence rate should be calculated: 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 Number of new events in a defined population over a defined period of time Total person-time at risk during the defined period of time When studying illness that last a short time (days or a few weeks), such as acute diarrhoea, then incidence would usually be the most appropriate measure. For more protracted diseases, such as the health effects of arsenic poisoning, prevalence would be the more appropriate measure. ESTIMATING DISEASE OCCURRENCE There are different approaches to estimating disease occurrence in a population. The choice of approach will depend on many different factors such as the amount of resources available and the accuracy of result required. Whatever approach is used, one of the most important starting points is to develop a case definition. Case definition The case definition is essential for both the epidemiological studies and any subsequent cost-benefit analyses. The case definition will enable the researcher to know whether or not a particular health event should be included in the analysis and will enable the cost-benefit analyst to determine the cost of the disease outcome. A case definition may be based on symptoms such as the presence of diarrhoea or clinical features of arsenic poisoning or the results of laboratory investigations such as whether or not a stool sample is positive for Cryptosporidium. For example, WHO defines diarrhoea as three or more loose or fluid stools (which take the shape of a container) in a 24 hour period (WHO 1993). Case definitions may also include age ranges, geographical location or dates of onset. Whatever case definition is used, it should be clear and standardised to minimise disease misclassification bias. Standardising case definitions becomes especially important when using more than one field researcher/interviewer/clinician or more than one community; this is because definitions of diarrhoea can be culture- and person-specific. For example, a 393 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 study conducted in a rural municipality in Nicaragua in Central America identified a classification encompassing nine different types of diarrhoea (Davey-Smith et al. 1993). The classifications used in Nicaragua were influenced by the place/person consulted for treatment. The source of any existing health care utilisation data should therefore always be carefully considered. Primary surveys Where prior information is not available or suspected to be unreliable it may be most appropriate to collect data directly from the population concerned. Such primary data is especially valuable for estimating the burden of disease for illnesses that are unlikely to cause people to visit their local health care provider. As such they are particularly valuable for self-reported diarrhoea. They can also be especially valuable in
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