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FIJI Post-Disaster Needs Assessment Table 12: Total Recovery and Reconstruction Needs for the ESLP Sector (F$ million) Recovery Reconstruction Resilience Total Micro-enterprise support and preparedness 7 7 Enterprise Recovery Programme (to support enterprises in the formal sector) 10 10 Expansion of existing social benefit scheme 7 7 Capacity building of Government agencies and CSO’s that support micro enterprises Skills Development & Business Confidence Programme for construction sector using Employment Intensive Infrastructure Programmes (EIIP) Child Labour monitoring, advocacy and withdrawal programme Study on the <strong>Fiji</strong> National Provident Fund (FNPF) on the impact of withdrawals for disasters and social security support programmes for informal workers 3.5 3.5 3 3 0.5 0.5 0.5 0.5 Total 31.5 31.5 Source: Estimations by Assessment Team. Note: A detailed breakdown of recovery needs by sector is included in Annex 2. 2.3 Disaster Impact on Quality of Life While the overall economic impact of disasters varies widely, it is always significantly negative on the quality of life of the affected population, particularly in the case of more vulnerable population groups. Reliable quantitative procedures exist to estimate disaster impact at the macroeconomic level, but methodologies to quantitatively estimate disaster impact at the personal or household level have lagged behind, often concentrating only on qualitative means of assessment. The Human Development Index (HDI) was used as a proxy quality of life indicator; however, the HDI is relatively static and does not lend itself to measuring impact on quality of life caused by a sudden disaster, and is not available in all countries nor at sub-national levels. To estimate the changes in quality of life following TC Winston, a composite measurement index was estimated based on relatively simple indicators, and data was collected during the relatively short duration of this PDNA. 42 This approach was successfully applied and tested during the recent PDNAs following the 2015 Nepal earthquake and Myanmar floods and landslides. 43 The following sectoral indicators are used in estimating disaster impact on quality of life for the affected population: disease outbreaks arising from the disaster; In addition to the above, whenever agricultural production losses were high in comparison to normal productions volumes, which may occur as a result of slow-evolving disasters, an additional indicator measuring food insecurity may be added. 42 Jovel, Roberto. Estimation of Disaster-Induced Losses to Define Post-Disaster Recovery Requirements, in Disaster Recovery: The Governance, Economics, and Social Impacts, Asian Disaster Management News, Volume 22, Asian Disaster Preparedness Center (ADPC), Bangkok, Thailand, 2015. 43 See Myanmar Post-Disaster Needs Assessment on Floods and Landslides, July–September 2015, Government of the Union of Myanmar, November 2015. 36 Tropical Cyclone Winston, February 20, 2016
FIJI Post-Disaster Needs Assessment Based on the values obtained for pre-disaster and post-disaster conditions for the above-listed sector indicators, and assigning equal weights to each, a composite indicator is developed that provides a measure of how the affected population’s quality of life deteriorated because of the disaster. Moreover, the estimated quality of life composite indicator may be used in the future as a measure of the degree of recovery being achieved over time. 2.3.1 Quantification of Sectoral Quality of Life Indicators During the 2016 <strong>Fiji</strong> PDNA, existing sectoral baseline information and the estimated value of the main disaster effects were used to define quality of life. Housing While information on pre-disaster housing deficits was not fully available, data was collected on the number of households existing in all disaster-affected provinces from the 2007 census and the most recent household survey. In addition, the number of fully destroyed housing units, together with those that sustained high partial destruction caused by the cyclone, was obtained from local and national authorities (Table 13). Housing units that sustained only minor damage were not considered for the analysis. Table 13: Pre- and Post-Disaster Housing Data in Disaster-Affected Provinces Province Pre-Disaster number of Housing Units Post-Disaster number of Houses Destroyed Major Damage Ba 47,533 3,494 4,241 Bua 2,794 524 605 Cakaudrove 7,858 1,513 2,199 Kadavu 2,161 0 0 Lau 5,897 328 63 Lomaiviti 2,517 1,191 296 Macuata 5,636 5 10 Nadroga 9,250 122 259 Naitasiri 25,240 542 365 Namosi 1,419 27 14 Ra 5,946 2,813 757 Rewa 16,426 66 78 Rotuma 639 0 0 Serua 2,596 19 19 Tailevu 10,378 395 287 Source: Estimations by Assessment Team. The housing index was estimated for pre-disaster and post-disaster situations (Table 14). Table 14: Pre- and Post-Disaster Housing Index by Province Province Pre-Disaster Post-Disaster Ba 1.0135 0.8485 Bua 0.9164 0.5461 Cakaudrove 0.8162 0.4307 Kadavu 0.9586 0.9586 Lau 0.4823 0.4504 Lomaiviti 0.9224 0.3780 Macuata 1.0785 1.0756 Tropical Cyclone Winston, February 20, 2016 37
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Damage to Ovalau Resort Source: Min
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