Acute Viral Hepatitis: Creating Awareness And Locating Buffer Zones For VaccinationMs.Chaitali Chandani (B.Tech computers), Email: chaitali_91@sify.com Ms.Priya Dagar (Bsc IT) Ms.Vijayalakshmi Patil (B.E. Electronics) Students Symbiosis Institute Of Geoinfrmatics, Pune viji_pa@rediffmail.com Abstract Acute viral hepatitis is a systematic infection affecting the liver predominantly .Almost all cases of acute viral hepatitis are caused by one of five viral agents: hepatitis A virus(HAV),hepatitis B virus(HBV),hepatitis C virus(HCV),hepatitis D virus(HDV),hepatitis E virus(HEV). A sixth agent ,hepatitis G virus(HGV),has been discovered ,but its role in acute viral hepatitis remains to be established .All these human hepatitis viruses are RNA viruses, except for hepatitis B, which is a DNA virus .It affects all age groups and can lead to liver disease, liver cancer and death in many of those afflicted. The virus is transmitted through blood , infected bodily fluids, direct blood-to-blood contact, unprotected sex, use of unsterile needles, and from an infected woman to her newborn during the delivery process. Hepatitis B is 100 times more infectious than the AIDS virus, yet it can be prevented with a safe and effective vaccine. A clear distinction among the different types of viral hepatitis can be made on the basis of clinical or epidemiologic features and specific serologic testing .GIS provides dynamic analysis tools and variety of display techniques which helps in faster and better analyses of epidemiological data, revealing trends, dependencies and inter-relationships that would be more difficult to discover in tabular format .By exploiting the full potential of this upcoming technology the public health administrators can provide 100 percent vaccination coverage to our own localities and also to ‘hardest to reach’ clients that is those families and communities living in remote areas ,the under-served and population segments living in municipal slums. The paper presents the framework of using GIS to generate thematic maps of acute viral hepatitis infected areas along with there types and intensity , create buffer zones around selected features and then combine this information with virus incidence data to determine how many cases fall within the buffer. By mapping the impact zone of vector breeding site , identifying catchment areas of health centers and by locating suitable site for a new health facility timely control activity can be strengthened .Dynamic maps can be displayed on internet which will assist patients to locate the most convenient health services easily from any anywhere even if they are not familiar with the technology. In a developing country like India , we had a Himalayan task to perform but awareness plays a very vital role in closing the immunity gap so that the transmission of the most crippling disease of this century- acute viral hepatitis could be terminated everywhere in the country. Eradication brings equity. Introduction Acute viral hepatitis is a systematic infection affecting the liver predominantly . Almost all cases of acute viral hepatitis are caused by one of five viral agents: hepatitis A virus(HAV),hepatitis B virus(HBV),hepatitis C virus(HCV),hepatitis D virus(HDV),hepatitis E virus(HEV). A sixth agent ,hepatitis G virus(HGV),has been discovered, but its role in acute viral hepatitis remains to be established.. Hepatitis B is 100 times more infectious than the AIDS virus, yet it can be prevented with a safe and effective vaccine. In some rare cases, the Epstein Barr Virus (which causes mononucleosis) can also result in hepatitis because it can cause inflammation to the liver. There are other viruses and bacteria that can also cause hepatitis including hepatitis D, E, varicella (chickenpox), and cytomegalovirus (CMV).  Problem statement: 4 million people in India every year die from one or the other form of acute viral hepatitis . Epidemics are almost exclusively of the entertically transmitted NANB (non-A and non-B) hepatitis .Hepatitis A (epidemic jaundice) is an infectious disease like poliomyelitic . but it can be cured . Fatality rate of 0.1% mainly in adults . Hepatitis B is endemic throughout the world especially in tropical and developing countries and also some regions of Europe . Lowest in countries with high standard of living like Australia , North America and Europe , and highest in countries or areas where socio-economic level is lower (eg. China , South East Asia, South America).More than 2 billion people have been infected with HBV globally , this figure includes some 325 million chronically infected carriers of the virus . HBV directly related to 1-2 million deaths per year . In India -1991,a total 93497 cases and 1449 deaths of viral hepatitis were reported ,which approx.30% to 40% are likely to be Hepatitis B. Studies conducted by National Institute Of Virology at Pune showed that the rate of chronic carrier of HBsAG varied . HBV was also implicated in a major epidemic outbreak in Ahmedabad Gujrat) in 1984.Total cases in epidemic was 1783 with an incidence of 59 per 1000 population and fatality rate of 15.6%.The areas which affected most in pune are slum areas which are located along river side. The prevalance and incidence of hepatitis B virus (HBV) infection among patients attending three STD clinics in Pune, India. Of the 2098 patients screened at STD clinics in Pune during 1996, 497, who returned for at least one follow up visit, were screened for various markers of HBV infection (HBsAg, anti-HBs, anti-HBc), HIV antibody, and VDRL. Study Area The study area taken is Pune covering an area of 138 Sq Km with a population of 2697425.According to geographical conditions district is divided into three parts:1)Towards west 15 to 30 kms Mountains known as Ghatmatta 2) Towards East of Ghatmatta 15 to 30 kms plane known as Maval 3) Towards East its Plane known as Desh.In summer the temperature is 22°C TO 41°C, Winter :8°C TO 25°C, Rainfall : 650 To 700 mm.There are 50 zones in Pune and the number of PHC(Pune Health Centers)are 50. Number of slums 553 and Declared slums 347.Water drainage per day 150 million liters .Geographic location is foothills of Sahyadri Mountains. Main river Bhima.and sub-rivers are Nira , Indrayani, Mula, Mutha, Vel, Ghod, Meena Kukdi, Pushpavati, Pavna. Here we have located 28 health centers and 93 slum areas on the map of pune district. Factors influencing Hepatitis Various factors are examined which influence the number of Hepatitis cases in Pune district. Major factors to influence the occurrence of Hepatitis cases are rainfall, temperature, humidity, and land use/land cover area (whether it is industrial area or vegetation ,or water body is present) . Average rainfall was obtained from the meteorological station provided by the Department of Meteorology, Ministry of Communication. These data were acquired with the government agencies and from published reports.  What causes Hepatitis? Hepatitis can be caused by several factors including chemical toxicity, drugs, alcohol, and most notably viral infections. The five common viruses causing hepatitis are: Viral Hepatitis A: Typically spread by eating food or drinking water contaminated with human feces. This is referred to as fecal-oral transmission. Viral Hepatitis B: Typically spread from mother to child at birth, through sexual contact, blood transfusions, or needles. Viral Hepatitis C: The most common of viral forms, typically spread through blood transfusions, needles, sexual contact, or working in a medical environment. Viral Hepatitis D: Spread only in the presence of hepatitis B and transmitted in the same ways. Viral Hepatitis E: Most commonly found in people who live in countries with poor sanitation. Liver inflammation can also be caused by medications, recreational drug use, severe chemical toxicity, and alcohol abuse. The risk of infection is greatest in developing countries with poor sanitation or poor personal hygiene standards. It is observed that most of the slum areas are along river. water plays very crucial role in spread of hepatitis A . So slum areas are at highest risk of getting affected .So government has to carry out Awareness programs and vaccination camps in slum areas under risk .also medical facilities has to be provided to those areas. It is observed that many hepatitis A cases go unregistered which occur in slum areas so slum areas have to be targeted for carrying out awareness programs and Vaccination camps. So our methodology will target slum areas in Pune district. Methodology: Our methodology is to target slum areas which do not come under PHCs buffer zone (i.e. areas which are not inside the buffer zone of 2Km around PHCs).Those areas would come under risk zone as those would not be at reachable distance in case of medical emergency and people would not be responsive to the awareness programs and vaccination camps arranged .So slums which come under this risk zone have to be provided with medical facilities. After locating all PHCs and slum areas on map we have to create buffer zone of 2Km around PHCs. Then risk probability for wards which contain slum areas under risk zone will be calculated since areas can be easily affected by the virus and need special attention by the PMC and social organizations as well. Then depending upon risk probability awareness program and vaccination camps would be suggested to government accordingly.  Maps provided by PMC (Puna municipal corporation) are digitized .The ward wise pune map is developed and PHCs and slums are located for risk zone and buffer analysis .The map after georeferencing is digitized using ARCVIEW 3.2a software .The map after the operation is shown below ,there are 50 wards in pune Here data analysis is done using an information value method. medical, administrative data is used for creating thematic maps .Then using Arcview software of GIS , risk zone map is prepared and then decisions are made accordingly. We will be using buffering operation to locate slum areas at high risk.  Case study : We have taken Pune district as our case study area.  Pune district ward wise population distribution On digitized map of pune district , PHCs are located .Then slum areas are located .Then buffering is carried out . Buffering around PHCs is done . Buffering: Buffering operation is carried out to determine slum areas which do not come under buffer zone of PHCs(Primary health centers).By creating 2Km buffer zone around PHCs we can detect slum areas which are at high risk .In following map Yellow points which are out of PHCs buffer zone are at risk  Risk zone map Total 19 slums are out of coverage area of PHCs RISK ZONES: Name of wards:
Calculating probability of wards getting affected because of slum areas under risk of hepatitis : Probability = No of slums under risk/Total number of ward Probability for Hadapsar ward=5/50=0.1 Ward name Number of slum areas Number of wards Probability Pashan 3 50 0.06 Aundh 2 50 0.04 Gokhale nagar 4 50 0.08 Kalas Dhanori 1 50 0.02 Kirloskarpneumatic 2 50 0.04 Hadapsar 5 50 0.10 Sangamwadi 1 50 0.02 Police ground 1 50 0.02  From this we can conclude that hadapsar ward which is having maximum slum areas is having highest risk of getting affected by Hepatitis as PHCs are not located near to any of the slum areas in Hadapsar . Special attention towards this ward need to be provided by government. Results and Discussion: From above conclusion can be drawn that In following slum areas which do not come under buffer zone of PHCs , Awareness programs and vaccination camps should be arranged .also medical facilities has to be provided to those areas:
Extrapolation techniques used vector distribution in inaccessible and unsampled areas of Pune which can be mapped using GIS( Dr. C.P. Johnson1 et al ,2001) Information value analysis method: Bayes' theorem has been frequently used in the areas of diagnostic testing and in the determination of genetic predisposition. P(A|B) = P(B|A)×P(A)/P(B). To know the probability of an area in Pune with a particular genetic profile of the people (ie there medical history from PMC) (D) which can develop hepatitis cases (H)—that is, P(H|D). Previous knowledge leads to the assumption that the probability of area being infected with the factors which can influence the virus is say (P(D)is 0.1 and the probability of cases being registered by the PMC in that area with the virus (P(B)) is 0.2. New evidence can be establishes which tells that the probability of the area having risk of getting affected with the disease is 0.5(P(B/A)).Thus: P(A|B) = 0.1×0.5/0.2 = 0.25. We c an also apply the formula P(H/D)=P(D/H) . P(H) P(D/H) . P(H) Where P(H/D)is Posterior probability,P(D/H)/P(D/H) is Individual Probability, P(H)/P(H) is Prior Probability. Different possible risk classes can be identified. These can be designated as very low, low, moderately low, moderately high, high and very high This can indicate which class has the maximum influence on the incidence of virus.From above we find slum areas which do not come under buffer zone of PHCs , there Awareness programs and vaccination camps should be arranged .also medical facilities has to be provided to those areas. Conclusion : GIS helps in Hepatitis Risk Zone analysis and buffer analysis to map the impact zones of which need the health care facility and it can also help to fully utilize the existing health care facilities .Awareness programs as well as vaccination camps can be held at the specified locations .Usually government puts equal money distribution for health care facilities in all areas .by using GIS government can put money on needy areas rather than having equal distribution of money and health care facilities every where. Health-care facilities, or strategies for addressing high-risk individuals or mobile carriers can all be better addressed through effective information management and visualization supported thus through a GIS. GIS integrates common database operations, such as query ,statistical analysis ,unique visualization and geographic analysis benefit offered by maps which make easier for the organization to take decisions , planning strategies and predicting outcomes .GIS being a powerful tool for examining population- level effects of services as reflected in geographical and spatial distribution of populations. Health-care facilities, or strategies for addressing high-risk individuals or mobile carriers can all be better addressed through effective information management and visualization supported thus through a GIS References:
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