Post Flood Health Relief Response: An experience from AIIMS Patna

Original Article Post Flood Health Relief Response: An Experience from AIIMS Patna Running Title: Post Flood Health Relief Shamshad Ahmad1, Abhishek Kumar1, Yogesh Kumar2, Anil Kumar3, Pallavi Lohani1, C M Singh1 1 Department of Community and Family Medicine, AIIMS, Patna, 2 Dept. of Physiology, AIIMS, Patna, 3Dept. of Trauma & Emergency, AIIMS, Patna, Corresponding Author: Dr. Abhishek Kumar Email: abhishekchaubeylalganj@gmail.com Abstract Background: There was unpredictable rain in September 2019 due to which, Patna, the state capital of Bihar, India experienced a devastating flood. There was indiscriminate damage to housing, communication and transport networks, and health facilities; affecting the lives of thousands of people. Objectives: To assess the morbidity profile of patients attending the health relief response camps conducted in different regions of Patna by AIIMS Patna team during the post-flood period. Methodology: On the direction of Government of Bihar to the administration of AIIMS, Patna, nine flood health relief response teams of AIIMS Patna were formed on the evening of 4th October 2019. All the required logistics were arranged within next 12 hours, and the teams started working from 5th of October 2019 for the next five days. Data were collected regarding age, gender, presenting health problems and history of any chronic diseases using Google forms. The total number of patients attending the camps during these five days were 3511. Real-time data analysis was done using cloud based google sheets. Results: In the camp, it was found that the common health problems reported by the cases were of itching (19.2%), followed by cough (14.7%), and fever (11.7%). About 13% (448) cases were having history of chronic non-communicable diseases. Maximum cases reported in our camp were on 8th October 2019, which was 1072 (30.5%). Conclusions: Rapid action by government and the health system averted epidemic outbreaks. Maximum cases were of itching in the camps Keywords: Health relief response, flood, disaster Introduction Floods are the most common disasters globally, and were responsible for 53,000 deaths worldwide in the last ten years. A flood causes major loss of both life and property. The resultant disturbance of transportation, communication and unavailability of clean water affects the human health [1]. The onset of a flood results in higher infectious disease burden. Flooding is associated with an increased risk of infection; population displacement, inadequate shelter conditions, degree of overcrowding, consumption of International Journal of Health Systems and Implementation Research-2020, Vol. 4(1) 55 Ahmad S et al contaminated water, improper sanitation, underlying health status of population, malnutrition, local disease ecology, and difficulty in access of health care services [2]. Bihar is located in the eastern region of India, it is an entirely land-locked state under the sub-tropical region of the temperate zone. It is bounded by Nepal in the north, and by the state of Jharkhand, India in the south. Rainy season occurs mainly from June to September; with a rain-fall ranging from 1250 mm to 1400 mm. There are two distinct regions which divide Bihar into two parts viz. north of Ganges river and south of Ganges river. Patna lies south of the Ganges river [3]. Being situated on the bank of river Ganges, Patna lies in an area liable to floods as per the flood hazard map (http://bmtpc.org/) of Bihar. Various infectious disease outbreaks have been reported following floods in developing countries, and these outbreaks vary in magnitude and rates of mortality [4]. Post Flood Health Relief Figure 01: Flood hazard map of the state of Bihar, India showing flood liable areas Methodology Study design – Cross sectional study Study setting – Nine different flood affected areas of Patna district, Bihar Study duration – 2 weeks Study participants – All the patients who came to the flood health relief response camp to seek medical advice were included. Sampling technique – Total enumeration This year in 2019, during the entire emergency period, the National Disaster Response Force (NDRF) team rescued two persons and evacuated 9490 persons. They provided medical assistance to 5806 needy people in Bihar. A total of 17 relief camps were run across the state on directives of the State Government; displaced people were accommodated in these relief camps [5]. With this background our study aimed to assess the morbidity profile of patients attending the health response camps conducted in different regions of Patna by AIIMS during the post flood period. Data collection - The questionnaire for data collection from the health response camps was developed using an online platform using Google forms. A ‘Whatsapp’ group of flood response team was formed. The online form link was shared on this group. Data from each camp was obtained through Google form and stored in Google spreadsheet. A dynamic dashboard (which changed with every data entry) was created for real-time data monitoring and to keep a check on patient flow at each mobile health unit. Study tools – Data collection was done regarding age, gender, presenting health problems and history of any chronic diseases. Statistical analysis – Finally the analysis of data was done using the SPSS (version 21) software. The results were expressed as frequency and percentage of the variables. International Journal of Health Systems and Implementation Research-2020, Vol. 4(1) 56 Ahmad S et al Post Flood Health Relief We used to generate a daily report once all units got closed for the day. Figure 02: Flood health relief response camps in Kankarbagh and Rajendra Nagar, Bihar, India Day 1 5th Oct • Camp started at 9 places as decided. • The team tried but it was not feasible to put camp for Premchand Rangalay and Bazar Samiti areas • Camp started in nearest feasible location i.e Vaishali Cinema Chauk Day 2 6th Oct • Camp continued at 9 places as above • Team tried to enter the bazar samiti area, succeeded a bit but still it is largely unreachable. • Bazar Samiti and Premchand locality was served through Vaishali Cinema Chauk, primarly. Day 3 7th Oct • Camp continued at 9 places as above. • Team gets access to Bazar Samiti and Premchand Rangalay. Local peoples were approached and treated then and there. • It was decided to put a formal camp in the closet vicinity of these area. Day 4 8th Oct Day 5 9th oct Figure 03: Flood health relief response camps near Kumhrar and Indrapuri, Bihar, India • 2 camps of lesser patient turn-out i.e Karbhighya and Baba Chauk were merged with Bazar Samiti camp in expectation of high demand for manpower and medicines there. The decision was found to be favourable, later. • At remaining places camp continued as such. • In afternoon, seeing the very low turn-out at Munna Chauk, the team was sent to Dinkar Chauk area due to high demand at the latter. • Camps continued as above. • Jakkanpur camp merged with Mithapur camp for better coverage. • Nehru Nagar camp merged with Rajiv Nagar camp for better coverage Figure 04: Day-wise schedule of the flood relief health response team Findings During the five-day camp, 496 person-days were contributed by AIIMS, Patna staff for flood-hit areas. On the 5th and 6th of October, 2019, patients from ‘Bazar Samiti’ areas were served from the nearest camp of Vaishali Chowk. Due to some network error data from the area of Rajiv Chowk could not be captured on first day. About 50 cases were treated this day. On later days some teams were merged for better resource allocation in severely affected areas. Execution Plan of the flood health relief response camp The relief teams attended a total of 3511 cases, during the five days of health camp. Table 1 shows the date-wise details of number of patients. About 13% (448) cases were having history of chronic noncommunicable diseases (diabetes, hypertension, asthma, Chronic Obstructive Pulmonary Disease & hypothyroidism) as shown in table 2. From table 3, it is evident that maximum cases were of itching (19.2%), followed by cough (14.7%), and fever (11.7%). About 6% cases presented with diarrhoea and loose stools, while 5% cases had weakness as their primary complaint. International Journal of Health Systems and Implementation Research-2020, Vol. 4(1) 57 Ahmad S et al Discussion Floods are caused by natural factors or by a combination of natural and human factors. Risk from a flood is the probability of loss, this can be expressed as: Risk = Hazard x Vulnerability [6, 7]. The hazards of flood depend on the magnitude of flood depth, velocity, and duration. Vulnerability may be defined as the conditions determined by physical, social, economic, and environmental factors, which increase the susceptibility of a community to the impact of hazards. If flood water enters the habitation of people and infrastructure, then the vulnerability of people and infrastructure is liable for harm and damage. In urban areas impact of floods are significant in terms of economic losses, both direct and indirect. This is due to high density of population, large impervious areas, clogged of drainage systems, high economic value of property and infrastructure, etc. Better flood emergency response mechanisms help reduce potential secondary losses. While in rural areas, the damages due to floods are mostly direct – in terms of loss of agricultural production. In our study it was found that the commonest complaint of cases were itching, followed by cough. In a similar study done after Chennai floods the most common cases were of acute respiratory infections, followed by gastroenteritis [8]. The results of a study done in Pakistan by Ahmad et al. showed that the distribution of infectious disease cases presented to relief camps were gastrointestinal cases (acute diarrhoea) – 30%, skin and soft tissue infection (33%), eye infection (Conjunctivitis) – 07%, ear, nose and throat infection (05%), respiratory tract infection (21%), and suspected malaria (4%) [9]. In another study done in Taiwan by Lin et al. there was a higher percentage of female cases (66.7%) than males (33.3%). Whereas, in our study more percentage was of male cases (70.6%) [10]. In a study done in Nepal by Kafle et al. it was found that waterborne infectious diseases and mental disorders were prominent diseases during Post Flood Health Relief the post-flood period [11]. However, in our study no mental disease case was reported. Our study was done only in some of the flood relief health response camps in certain areas of Patna district. The health response camps were arranged immediately after the flood and no follow-up health response camps were held in the same area. We conclude from the study that there were large number of cases of itching and fever, but there was no need for hospitalization for any of these cases. Some cases also had a history of chronic non-communicable diseases. Also, there was no epidemic of dengue or cholera or other waterborne diarrhoeal diseases. It is important to provide health relief response camps during floods, however basic sanitation and hygiene should also be maintained. Ethical Approvals Declaration of Helsinki have been followed throughout the study. Conflict of Interest None declared Acknowledgements We are thankful to State Government officials, medical superintendent of AIIMS, Patna, faculty members for their guidance and support. We also thank residents, interns, MBBS students, nursing officers and ambulance, vehicle drivers for putting all their efforts to make the flood health response camps successful. There was no financial support in this study. References 1. Menon et al. Study of morbidities in a flood relief camp: observations from kerala 2018. European Journal of Pharmaceutical and Medical Research 2018;5(11):443-445 2. Watson JT, Gayer M, Connolly MA. Epidemics after Natural Disasters. Emerg Infect Dis 2007;13(1):1-5. International Journal of Health Systems and Implementation Research-2020, Vol. 4(1) 58 Ahmad S et al 3. Government of India, Ministry of Micro, Small and Medium Enterprises, BIHAR STATE PROFIE, 2015-16 http://dcmsme.gov.in/dips/state_wi se_profile_16-17/Bihar%20 %20State%20Profile.pdf [Last accessed on 31/01/2020] 4. Ministry of Home Affairs Disaster Management Division (National Emergency Response Centre) Situation report on Flood/Heavy Rain fall as on 30th September, 2019 at 1800 Hrs. https://www.ndmindia.nic.in/image s/gallery/Situation%20report%20as %20on%2030.09.2019%20at%201 800%20Hrs.pdf[Last accessed on 31/01/2020] 5. Mondal NC, Biswas R, Manna A. Risk factors of diarrhoea among flood victims: A controlled epidemiological study. Indian J Public Health 2001;45:122-127. 6. Srikantha Herath, Geographical information systems in disaster reduction, Institute of Industrial Science, The University of Tokyo, Japan; 2001. 7. Tingsanchali T, Keokhumcheng Y. Flood damage functions for surrounding area of Second Bangkok International Airport, Proceedings, International Symposium on Urban Safety of Post Flood Health Relief Mega Cities in Asia, Phuket, Thailand, November, 2006; p. 291300. 8. Angeline N, Anbazhagan S, Surekha A, Joseph S, Kiran PR. Health impact of Chennai floods 2015: Observations in a medical relief camp. Int J Health Syst Disaster Manage [serial online] 2017 [cited 2018 Oct 6]; 5: 46-8. 7. Available from: http://www.ijhsdm.org/text.asp?20 17/5/2/46/213887 [Last accessed on 01 feb 2020] 9. Z, Khan AA, Nisar N. Frequency of infectious diseases among flood affected people at district Rajanpur, Pakistan. PJMS, 2011; 27: 866-9. Available from: http://www.pjms.com.pk/index.php /pjms/article/view/975. [Last accessed on 01 feb 2020]. 10. Lin C, Chen T, Dai C, et al Serological investigationto identify risk factors for post-flood infectious diseases: a longitudinal survey among people displaced by Typhoon Morakot in TAIWAN BMJ Open, 2015; 5: e007008. doi: 10.1136/bmjopen- 2014-007008. 11. Kafle KR, Dahal RK, Khanal SN. Postdisaster epidemiological assessment of Koshi flood 2008, in Nepal. Int J Health Syst Disaster Manage 2016;4:15-24 International Journal of Health Systems and Implementation Research-2020, Vol. 4(1) 59 Ahmad S et al Post Flood Health Relief Table 1: Number of cases attending the camps according to locations (n=3511) Dates Oct-5 Oct-8 48 Oct-6 30 Oct-7 60 Bazar Samiti Chauk 26 102 60 406 116 710 Dinkar Chauk 38 84 77 108 103 410 Jakkanpur 19 23 39 61 Karbighaiya 34 38 80 Kumhrar Park 68 74 94 62 Mithapur 39 42 37 70 Munna Chauk 40 23 37 16 Nehru Nagar Chauk 28 83 87 79 52 98 121 135 119 149 686 788 Team Location Baba Chauk Rajiv Nagar Chauk Vaishali Cinema Chauk 36 376 Grand Total Oct-9 Grand Total 138 142 152 1072 298 67 255 116 122 399 271 181 620 589 3511 Table 2: Cases with non-communicable diseases during 5 days of camp Case Frequency Percentage (%) Diabetes 132 3.7 Hypertension 218 6.2 Asthma/COPD 42 1.2 Hypothyroidism 56 1.6 Total 448 12.7% Table 3: Gender wise distribution of patient complaints (n=3511) Gender Primary Complaint Abscess Backache Breathlessness Chest Pain Cough Diarrhoea Dizziness Dysentery Female (%) 3 (0.08%) 33 (0.93%) 18 (0.51%) 14 (0.39%) 145 (4.12%) 54 (1.53%) 25 (0.71%) 10 (0.28%) Male (%) 11 (0.31%) 55 (1.56%) 32 (0.91%) 39 (1.11%) 374 (10.6%) 162 (4.61%) 50 (1.42%) 18 (0.51%) Grand Total (%) 14 (0.39%) 88 (2.5%) 50 (1.4%) 53 (1.5%) 519 (14.8%) 216 (6.2%) 75 (2.1%) 28 (0.8%) International Journal of Health Systems and Implementation Research-2020, Vol. 4(1) 60 Ahmad S et al Fever Headache Injury Itching Pain abdomen Pain-Generalized Pain-Localized Rash-Generalized Rash-Localized Swelling Taenia Infection Ulcer/Wound Upper Respiratory Tract Infection Urinary Tract Infection Vomiting Weakness Grand Total Post Flood Health Relief 119 (3.38%) 49 (1.39%) 14 (0.39%) 142 (4.04%) 67 (1.9%) 60 (1.7%) 89 (2.53%) 13 (0.37%) 13 (0.37%) 12 (0.34%) 11 (0.31%) 22 (0.62%) 294 (8.37%) 89 (2.53%) 74 (2.1%) 533 (15.18%) 105 (2.99%) 105 (2.99%) 192 (5.46%) 13 (0.37%) 30 (0.85%) 38 (1.08%) 27 (0.76%) 82 (2.33%) 413 (11.7%) 138 (4%) 88 (2.5%) 675 (19.2%) 172 (4.9%) 165 (4.7%) 281 (8%) 26 (0.7%) 43 (1.2%) 50 (1.4%) 38 (1.1%) 104 (3%) 23 (0.65%) 26 (0.74%) 49 (1.4%) 2 (0.05%) 19 (0.54%) 74 (2.1%) 1031 (29.4%) 6 (0.17%) 26 (0.74%) 99 (2.81%) 2480 (70.6%) 8 (0.2%) 45 (1.3%) 173 (5%) 3511 (100%) -----*----- International Journal of Health Systems and Implementation Research-2020, Vol. 4(1) 61