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\title{Rapid Need Assessment of District Srinagar, Post September 2014 Floods}
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             \author[1]{Sheema  Samreen}

             \author[2]{Muzamil  Hassan}

             \author[3]{S.M. Salim  Khan}

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\date{\small \em Received: 12 December 2018 Accepted: 4 January 2019 Published: 15 January 2019}

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\begin{abstract}
        


Introduction: Natural disasters are common worldwide and cause huge damage. Floods are among frequent natural disasters. Torrential rainfall due to the combined effect of western disturbances and monsoons led to floods in September 2014 in Jammu and Kashmir.Objective: This cross-sectional descriptive study was conducted in District Srinagar 45 days after floods. It was a rapid need assessment done for assessing the health and safety needs of the population.Methods: 30 x 7 cluster sampling based on the Community Assessment for Public Health Emergency Response (CASPER) methodology was used to select seven households from 30 census blocks using two-stage sampling. Data collection was done on demographics, damage, prepare-dness and needs.

\end{abstract}


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\let\tabcellsep& 	 	 		 
\section[{Introduction}]{Introduction}\par
atural disasters are common worldwide and threaten the life of people. Globally, flood is the most frequent and exorbitant disasters (1) (2) \hyperref[b3]{(3)}. Assessment of needs of affected people following disasters is a first line public health response for designing and prioritization of emergency policy. (4) (5) Rapid need assessments (RNAs) are first tool of survey following disasters which steer response efforts to emergencies especially in the recovery phase. (4) \hyperref[b5]{(5)} The Centers for Disease Control and Prevention (CDC), Atlanta developed a toolkit known as Community Assessment for Public Health Emergency Response (CASPER) for RNAs in 2009 so that on time, valid and economic position of current household-based public health needs could be ascertained during disasters. (4) \hyperref[b6]{(6)} Kashmir Valley is prone to floods because of its geographical location and topographical features as has been witnessed in past. \hyperref[b7]{(7)} The state of Jammu and Kashmir witnessed one of the devastating floods of history in the September 2014 which affected about million people directly. \hyperref[b8]{(8)}  \hyperref[b9]{(9)} The relentless rainfall for five days caused by the combined wrath of western disturbances and monsoon in the state of Jammu and Kashmir led to flooding of Jhelum River. (4) (7) \hyperref[b8]{(8)} The flood affected both urban and rural areas, submerging about 2600 villages, completely or partially, and larger part of the capital city Srinagar city. The flood caused massive damage not only to infrastructure, roads, and communication but even to some of major tertiary hospitals. (4) \hyperref[b9]{(9)} In some parts of Srinagar which were low-lying the water receded after a month. \hyperref[b7]{(7)} So keeping above facts into mind this study was undertaken 45 days after floods using CASPER toolkit with the main aim of assessing the impact of floods on health, needs of population besides assessing public health response after floods. 
\section[{II.}]{II.} 
\section[{Methodology}]{Methodology}\par
This was a cross-sectional study done after 45 days of floods from 20 October, 2014 to 25, October 2014 in the city of Srinagar. As per census 2011 the population of Srinagar city consists of 1,236,829 people and 188,645 households. The study was done as per the protocol given by CASPER toolkit which uses 30 x7 two -stage cluster sampling methodology with design effect "2" for collection of relevant data on the health status and basic needs at household level.\par
In order to select the desired 210 households for the study the methodology as described by CASPER toolkit was followed. In first stage, line listing of all housing units within 2011 census blocks of Srinagar was done and then 30 clusters were randomly selected by probability proportional to size. In second stage, household was selected for interview by going to center of the selected cluster and then moving in a random direction which was decided by spinning a pen. The direction of the pen was followed to interview every 10 th household until the required seven households were selected for the study.\par
The data was collected by five teams with two members each in the team who had received training on data collection. A modified questionnaire used for data collection was prepared from the CASPER question bank.\par
The questionnaire captured information regarding domains such as demographics, functional N needs, post-flood damage and repair, supply needs, emergency preparedness, concerns about injuries and illnesses, communication and needs.\par
After entering the household, explaining the objectives of the study and obtaining verbal consent from head /family member (>18 years) a detail interview was done for data collection.\par
The data was entered and analyzed in Epi -Info 7 software. The data analysis was done using households as units of analysis. Then weighted proportions were calculated using mathematical weight for probability of selection of each interviewed household using formula:\par
"weight" ="total number of housing units in sampling frame"/number of housing units interviewed within clusters x number of cluster selected Using the weighted proportions, estimated projections and confidence intervals (CI) were calculated after taking in account the differences within and between the clusters.\par
Furthermore, contact rate and completion rate of interviews were also calculated by dividing the completed interviews by the total number of households where contact was attempted, and by dividing the number of completed interviews by the number of interviews conducted. 
\section[{III.}]{III.}\par
Results  In this study 213 households were contacted and 210 interviews were completed giving contact rate of 98.5\% and completion rate of 100\%.\par
In this study demographics revealed that there was vulnerable population in the households such as elderly, children less than 5 years, lactating mothers, pregnant women and persons with serious difficulty in hearing, blindness and locomotor disability. Regarding health status about 81.43\% (153611) households were found to have at least one member who was on regular prescription medications for non-communicable diseases Emergency, Preparedness, Communication and Needs. Majority (60\%) were taking prescription medicines for hypertension followed by diabetes mellitus 30.95\%, 24.76\% for hypothyroidism and 3.33\% for asthma. (Table \hyperref[tab_0]{1})\par
Table \hyperref[tab_1]{2} reveals that about 59.03 \% (111391) had evacuated there house during or before floods and majority (71\%) had moved to friends or relatives home. About 12\% of houses were significantly damaged and 22.38\% felt that it was not safe to live in their houses. About 6.1\% were not residing in their homes at the time of survey. Only 5.7\% of households were insured and compensation was paid to less than 1\% of households.\par
This study also showed that more than 50\% of houses had musty or moldy odor while as about 75\% of households which had evacuated house during floods required assistance for repair .(OR: 9.3; CI4.9-17.7).\par
The table \hyperref[tab_2]{3} shows that that even after 45 days of flood basic amenities like food, water and electricity were lacking in some households and about 4492 households lacked food for next three days and just 17068 households had weekly supply of prescribed medicines.\par
Table \hyperref[tab_3]{4} shows although almost 75\% of households didn't have chlorine tablets but 100\% of the households in the region consumed boiled water as a routine practice in the region. Communication services of mobile network were restored in most of the areas but was lacking in about 1.5 \% of households. 51\% of the households had sought medical treatment during floods. The majority of the households had visited local health camps mostly for the ailments of cough, fever and diarrhea. About 41\% of households reported increased anxiety among at least one family member. Anxiety was more among those who had evacuated the house (OR=1.75, p =0.5) While assessing the immediate need at the time of study overall, 43\% (79950) households expressed need of financial help followed by no need (21\%) and need for basic commodities -including ration (17\%). While comparing the immediate needs of evacuated households with that of non evacuated, 53.26\% had a need of financial help, 17.2\% had need for and 11.29 \% had no need vis -a vis 26.4\%, 17.56 and 26.74\% of latter households.\par
IV. 
\section[{Discussion and Conclusion}]{Discussion and Conclusion}\par
The cross-sectional study was done after 45 days of Kashmir floods in September 2014, in order to assess the immediate needs of the households of district Srinagar. Rapid need assessment surveys are useful to collect timely data in a short period of time. The CASPER methodology by CDC was used in India for the first time during Kashmir floods by rapid assessment team from National Center for Disease Control, New Delhi three weeks after the floods (4).\par
This study found that vulnerable population was present in most of the household's. The vulnerable population has special needs and during disaster care ought to be taken for protection of health and prevention of malnutrition after floods. It was also seen that 80\% of the population was on prescribed medicines especially for the non-communicable diseases. Chronic diseases get exacerbated during disasters and can contribute to mortality \hyperref[b10]{(10)}. Non-communicable diseases (NCD) are leading cause of mortality worldwide so disaster preparedness and response needs to have a provision for management and treatment of NCDs. \hyperref[b11]{(11)}  \hyperref[b12]{(12)} The study revealed that more than half of the population had evacuated their households and about similar number of households were damaged, though most of these were habitable. In this study it was found that majority of houses had a moldy or musty odor which is common after floods and have been reported in studies done in America after Hurricane like Katrina but can be dangerous to the inmates and cause serious health effects if not taken care off on time. \hyperref[b13]{(13)} In this study it was revealed that even after one and a half month post floods households lacked basic commodities like food, water and electricity. Although reports reveal that huge supplies and commodities were procured by the government and non-government agencies, the study shows that supplies were not distributed in a proper way and post flood measures were not up to mark \hyperref[b14]{(14)}. There was also shortage of prescribed medicines in the households which is similar to findings of other studies and signifies the importance of disaster preparedness as stressed by United Nations in the Sendai Framework for Disaster Risk Reduction 2015-2030 (4) \hyperref[b15]{(15)}.\par
As documented by other rapid need assessment studies done after disasters worldwide, this study also revealed that there was increase in the mental health symptoms such as anxiety, nightmares ,agitation or depression among household member after floods (4) (16) (17) \hyperref[b18]{(18)}.\par
Lastly this CASPER tool helped to assess the immediate needs of the households at the time of study. The data can help in further planning and future disaster management strategy of the state for risk mitigation and post flood rehabilitation.\par
The strength of this study lies in the fact that useful and large set of data was collected in short period of time, which will help the state for framing future policy for disaster management.\par
Limitation of the study is that most of the questions of this study were self -reported and verification couldn't be done. Also sampling and analysis was done on the basis of households and not on individual level.\begin{figure}[htbp]
\noindent\textbf{1} \par 
\begin{longtable}{P{0.2869951534733441\textwidth}P{0.1098546042003231\textwidth}P{0.12907915993537963\textwidth}P{0.22794830371567043\textwidth}P{0.09612277867528271\textwidth}}
Vulnerable Population in Household\tabcellsep Projected Frequencies\tabcellsep Projected Percentages\tabcellsep Confidence Interval\tabcellsep Design Effect\\
Pregnant Women\tabcellsep 8984\tabcellsep 4.76\%\tabcellsep 1-8.524\tabcellsep 1.572\\
Lactating Mother\tabcellsep 36830\tabcellsep 19.52\%\tabcellsep 13.26-25.783\tabcellsep 1.256\\
Children < 5 Years\tabcellsep 76357\tabcellsep 41\%\tabcellsep 34.35\% -47.65\%\tabcellsep 1.2\\
Elderly > 65 Years\tabcellsep 89831\tabcellsep 48\%\tabcellsep 41.24\% -54.76\%\tabcellsep 1.67\\
Locomotor Disability\tabcellsep 6289\tabcellsep 3.33\%\tabcellsep 1.060-5.607\tabcellsep 0.808\\
Blind\tabcellsep 2694.9\tabcellsep 1.43\%\tabcellsep -0.705-3.562\tabcellsep 1.629\\
Deaf\tabcellsep 8085\tabcellsep 4.29\%\tabcellsep 0.828-7.743\tabcellsep 1.468\\
On Regular Prescribed Medicines\tabcellsep 153611\tabcellsep 81.43\%\tabcellsep 75.899-86.958\tabcellsep 1.019\\
Hypertension\tabcellsep 113187\tabcellsep 60.00\%\tabcellsep 32.380-67.620\tabcellsep 1.219\\
Hypothyroidism\tabcellsep 46712\tabcellsep 24.76\%\tabcellsep 17.091-32.433\tabcellsep 1.591\\
Diabetes Mellitus\tabcellsep 58391\tabcellsep 30.95\%\tabcellsep 25.003-36.902\tabcellsep 0.834\\
Asthma\tabcellsep 6289\tabcellsep 3.33\%\tabcellsep 1.06 -5.60\tabcellsep 0.808\end{longtable} \par
 
\caption{\label{tab_0}Table 1 :}\end{figure}
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\noindent\textbf{2} \par 
\begin{longtable}{P{0.25092592592592594\textwidth}P{0.12314814814814815\textwidth}P{0.08981481481481482\textwidth}P{0.11388888888888889\textwidth}P{0.19166666666666665\textwidth}P{0.08055555555555555\textwidth}}
\multicolumn{2}{l}{Variables}\tabcellsep Projected Frequencies\tabcellsep Projected Percentages\tabcellsep Confidence Interval\tabcellsep Design Effect\\
\multicolumn{2}{l}{Evacuated house during/before floods}\tabcellsep 111391\tabcellsep 59.05\%\tabcellsep 45.720-72.375\tabcellsep 3.7\\
Place of evacuation during floods\tabcellsep Friends/relatives Others Shelter\tabcellsep 79052 18865 13475\tabcellsep 70.97\% 16.94\% 12.10\%\tabcellsep 59.680-82.255 7.590-26.281 2.856-21.337\tabcellsep 2.354 2.354 2.354\\
\tabcellsep Minimal/none\tabcellsep 91628\tabcellsep 48.57\%\tabcellsep 35.904-61.239\tabcellsep 3.236\\
\tabcellsep Damaged but habitable\tabcellsep 73662\tabcellsep 39.05\%\tabcellsep 28.179-49.916\tabcellsep 3.236\\
Damage to home\tabcellsep Damaged and inhabitable\tabcellsep 17967\tabcellsep 9.52\%\tabcellsep 4.636-14.42\tabcellsep 3.236\\
\tabcellsep Destroyed\tabcellsep 5390\tabcellsep 2.86\%\tabcellsep -0.069-5.784\tabcellsep 3.236\\
\multicolumn{2}{l}{Feel that house is NOT safe for living}\tabcellsep 42221\tabcellsep 22.38\%\tabcellsep 14.733-30.025\tabcellsep 1.696\\
\multicolumn{2}{l}{Insurance of house}\tabcellsep 10780\tabcellsep 5.71\%\tabcellsep 1.167-10.261\tabcellsep 1.933\\
\multicolumn{2}{l}{House surveyed for damage assessment}\tabcellsep 7187\tabcellsep 3.81\%\tabcellsep 0.700-6.919\tabcellsep 0.996\\
\multicolumn{2}{l}{Compensation paid for damage to house}\tabcellsep 1797\tabcellsep 0.95\%\tabcellsep -0.399-2.304\tabcellsep 0.996\\
\multicolumn{2}{l}{Moldy musty odor}\tabcellsep 101509\tabcellsep 53.81\%\tabcellsep 42.129-65.490\tabcellsep 2.767\\
In need of any\tabcellsep Cleaning up the House\tabcellsep 66475\tabcellsep 35.24\%\tabcellsep 24.409-46.067\tabcellsep 2.58\\
assistance for house\tabcellsep Repair of house\tabcellsep 97916\tabcellsep 51.90\%\tabcellsep 39.022-64.788\tabcellsep 3.349\end{longtable} \par
  {\small\itshape [Note: K© 2019 Global Journals]} 
\caption{\label{tab_1}Table 2 :}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{3} \par 
\begin{longtable}{P{0.31378504672897195\textwidth}P{0.10724299065420559\textwidth}P{0.12908878504672897\textwidth}P{0.20654205607476636\textwidth}P{0.0933411214953271\textwidth}}
Variables\tabcellsep Projected Frequencies\tabcellsep Projected Percentages\tabcellsep Confidence Interval\tabcellsep Design Effect\\
No Electricity\tabcellsep 4492\tabcellsep 2.38\%\tabcellsep -0.070-4.832\tabcellsep 1.302\\
No Tap Water\tabcellsep 899\tabcellsep 0.48\%\tabcellsep -0.492-1.444\tabcellsep 0.996\\
No Food For Next Three Days\tabcellsep 4492\tabcellsep 2.38\%\tabcellsep 0.364-4.398\tabcellsep 0.882\\
No Accessible Toilet\tabcellsep 13475\tabcellsep 7.14\%\tabcellsep 3.010-11.275\tabcellsep 1.76\\
Received Relief Water\tabcellsep 60187\tabcellsep 31.90\%\tabcellsep 19.487-44.323\tabcellsep 3.575\\
Received Relief Food\tabcellsep 1068989\tabcellsep 56.67\%\tabcellsep 43.125-70.209\tabcellsep 3.762\\
Weeks Supply Of Prescribed Medicine\tabcellsep 17069\tabcellsep 9.05\%\tabcellsep 3.773-14.322\tabcellsep 1.094\end{longtable} \par
 
\caption{\label{tab_2}Table 3 :}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{4} \par 
\begin{longtable}{P{0.2336424957841484\textwidth}P{0.07596964586846543\textwidth}P{0.1118043844856661\textwidth}P{0.1333052276559865\textwidth}P{0.2221753794266442\textwidth}P{0.07310286677908938\textwidth}}
\tabcellsep Variables\tabcellsep Projected\tabcellsep Projected\tabcellsep Confidence\tabcellsep Design\\
\tabcellsep \tabcellsep Frequencies\tabcellsep Percentages\tabcellsep Interval\tabcellsep Effect\\
\multicolumn{2}{l}{First Aid Kit At Home}\tabcellsep 17967\tabcellsep 9.52\%\tabcellsep 4.005-15.042\tabcellsep 1.780\\
\multicolumn{2}{l}{Emergency Preparedness Kit}\tabcellsep 29643\tabcellsep 15.71\%\tabcellsep 7.109-24.320\tabcellsep 2.816\\
\multicolumn{2}{l}{Chlorine Tablets No}\tabcellsep 140137\tabcellsep 74.29\%\tabcellsep 65.39-83.192\tabcellsep 2.087\\
\multicolumn{2}{l}{Message To Boil Water}\tabcellsep 161696.\tabcellsep 85.71\%\tabcellsep 79.678-91.750\tabcellsep 1.49\\
\multicolumn{2}{l}{No Working Mobile Phones}\tabcellsep 2695\tabcellsep 1.43\%\tabcellsep -0.384-6.098\tabcellsep 1.907\\
\multicolumn{2}{l}{Sought Medical Care}\tabcellsep 106001\tabcellsep 56.19\%\tabcellsep 44.944-67.437\tabcellsep 2.588\\
\multicolumn{2}{l}{Experienced Anxiety}\tabcellsep 76357\tabcellsep 40.48\%\tabcellsep 30.169-50.784\tabcellsep 2.221\\
\tabcellsep Financial Help\tabcellsep 79950\tabcellsep 42.38\%\tabcellsep 30.256-54.504\tabcellsep \\
\tabcellsep No Need\tabcellsep 39526\tabcellsep 20.95\%\tabcellsep 12.361-29.544\tabcellsep \\
Immediate\tabcellsep Basic Commodities\tabcellsep 14373\tabcellsep 7.62\%\tabcellsep 3.078-12.161\tabcellsep 1.476\\
Needs\tabcellsep Ration\tabcellsep 17967\tabcellsep 9.52\%\tabcellsep 4.098-14.949\tabcellsep \end{longtable} \par
 
\caption{\label{tab_3}Table 4 :}\end{figure}
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