These impacts, and especially indirect spillovers to households not directly affected, are related to land use in affected regions and access to sanitation and hygiene. Smith et al. 2009) modeled the economic impact of flu in Britain, while another study examined the income impact associated with an outbreak of SARS (Keogh-Brown and Smith, 2008). For example, research in poorer countries has mapped the direct costs of disease due to waterborne diseases in Pakistan or the overall economic burden of waterborne diseases in Kiribati in the South Pacific (Malik, et al. 2012; and ADB, 2014). respectively).
The average annual rainfall varies from less than 900 mm in the driest parts (Southeastern and Northwestern) to more than 5000 mm in the wettest parts (western slopes of the Central Highlands). According to the World Bank data (2015), this is comparable to the health expenditure of countries such as Bangladesh and the Philippines which are in the same income category, and upper-middle income countries such as Fiji and Thailand. The survey questionnaire also asked whether the households had been affected by flood or drought in the past year.
11% of them live in areas affected by floods and 14% by drought in the month before the survey was conducted. These effects can lead to worsening health outcomes for people not directly affected by the flood/drought, but who live near directly affected households. We use household health expenditure data collected in the survey to estimate the private costs of health impacts from natural disasters.
In the final step, the mean number of inpatients and outpatients due to drought and flooding at the district level is calculated using the marginal effect estimated in our models, and the mean number of inpatients and outpatients in the district associated with extreme weather.
Results
Once again, the only statistically observable interaction term is that related to the effects of widespread (indirect) flooding and access to drinking water. To examine the role of spatial land use factors, we estimate specifications (vi) and (vii) by replacing district fixed effects with district-level land uses: Agricultural Water Catchment Areas and Larger Water Catchment Areas the water. Agricultural catchment areas include irrigated and rain-fed plains that act as low water catchment areas during rain.
Once we control for the presence of large areas of water retention, the overflow coefficient is no longer statistically or materially significant; this remains the case when the water retention control interacts with the overflow indicator (column vii). However, the direct adverse effect of flooding on hospital treatment is strong until water retention control is included, with an estimated increased probability of 11%. As with the previous analysis of flood risk and hospital care, there is some evidence that sanitation is associated with higher use of health services for households that report being directly affected and those defined as 'overflow' households in our framework.
14| Page e These results remain when we control for land use, and the interaction between land use and hazard occurrence. In this caseβcolumns (vi) and (vii)βthe coefficient for the land use and the interaction terms are sometimes statistically significant, but their actual size is quite small. It therefore appears that in the case of outpatient services and flooding, land use indicators (at district level) do not exert much influence.
As we previously observed for inpatient care, the probability of requiring outpatient services following a drought is statistically and materially significant and greater than the increase associated with floods. In these, we estimate the average increase in household-level health expenditure associated with an episode of hospitalization or outpatient health service utilization. Other interesting observations emerging from these estimates are that the costs associated with men and older patients are higher (on average).
Households with higher socioeconomic status (more educated, belonging to the Sinhalese majority, having higher incomes, and being urban) are all associated with higher health expenditures related to inpatient and outpatient care. To estimate the overall costs associated with health services provided to the population affected by the hazard, we need to measure the vulnerability of the population to the use of health services caused by floods and droughts across districts; These estimates are given in The estimated realization of the health burden at the district level is derived from the population in each district in each year and whether the districts are actually exposed to floods and droughts in the same year.
Conclusions, Caveats, and Climate Change
This district-level population susceptibility to adverse health due to flood and drought is calculated by multiplying the district average health risk, the district population and the point estimates of the disaster shock variable (marginal effect of flood and drought on health service utilization) as estimated in the regressions detailed above. Public health costs are based on the reported district level per capita health expenditure; while the private costs are estimated in table 6. 16 | Page possible epidemiological explanations for our flooding finding is the increased presence of disease-transmitting vectors (eg, mosquitoes) in the wake of floods, an increase that also affects households not directly damaged by the event.
Overall, our estimates show that Sri Lanka spends US$52.8 million per year on health care costs related to floods and droughts, which is almost equally divided between the public and household sectors and 22% against. Worryingly, our calculations show that the health burden is distributed spatially, with the highest per capita burden experienced by the Uva, North, North Central and East regions, which are located in the dry zone of Sri Lanka (Figure 2). Western Province is the wealthiest region in the country, with almost double the per capita monthly income of these provinces, and also bears the lowest per capita health burden related to floods and droughts.
It is worth noting that the estimated burden of health expenditure determined in this paper is only a part of the full economic cost of this health burden. The currency conversion is 1 USD=130 n Sri Lanka Rupee which is according to the exchange rate in 2013. Weather and mortality: a 10-year retrospective analysis of the Nouna Demographic and Health Surveillance System, Burkina Faso.
Intergovernmental Panel on Climate Change [Field, C.B., V.R. Cambridge University Press, Cambridge, UK and New York, NY, USA, 1132 pp. Six climate change-related events in the United States were responsible for about $14 billion in lost lives and health costs. 2011). The impacts and socio-economic costs on health in Europe and the costs and benefits of adaptation.
Contribution of Working Group II to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change [Field, C.B., V.R.
