Position paper on Hepatitis B

Issues Related to Hepatitis B Vaccination in India: Systematic Review of Literature

Background Note prepared by Dr. Jacob Pulliyel for National Consultative Meeting on Immunization convened by Indian Medical Association in May, 2006

Executive Summary

Background

A systematic review of literature forms the basis of this position document. Experts from all over the country will be invited to review the paper and contribute by enlarging the draft with other references from literature

Objectives

• To assess the prevalence of Hepatitis B in the country, and collect available data on deaths from hepatocellular carcinoma.
• To evaluate what the immunization program will cost the country.
• To look for evidence of the success of the pilot project.
• To collect evidence from world wide literature on the results of Hepatitis B vaccination starting at 6 weeks.

Search Strategy

Searches were made of the in Medline, Cochrane Library and Best bets and previous reviews, including cross references.

Data Analysis

Done using standard Meta analysis software

Main results

1. The true prevalence of Hepatitis B carrier rate, in non-tribal populations in India is 2.1 (CI 1.8-2.5). Among tribal populations it is 19.4 (15.3–23.5)
2. The death rate from Hepatocellular carcinoma is very low in the country and constitutes 1.6% of all cancer deaths.
3. The pilot project has not been evaluated properly.
4. The proposed schedule of immunization starting at 6 weeks has not been shown to be efficacious (in reducing prevalence) in any country in the world.
5. The cost outlay for universal immunization in India is Rs 500 crores each year.

Author’s Conclusions

An evaluation of the pilot project is required before the Government of India decides to incorporate Hepatitis B immunization in the EPI. The data required are:

1. Coverage (with 3 doses of Hepatitis B vaccine) in the pilot area.
2. The fall in carrier rate in the pilot study area
3. Carrier rate among those immunized at 6 weeks compared to those immunized at birth

This is essential because the proposed schedule of immunization starting at 6 weeks, has not been shown to be efficacious (in reducing prevalence) in any country in the world.

Plain Language Summary

The pilot project areas can provide useful data on feasibility, cost and efficacy of the Hepatitis B vaccination program starting at six weeks. It is difficult to defend the incorporation of Hepatitis B vaccine in the EPI without evaluating experience from the pilot project. More research is needed, especially as there is no data in literature that vaccination starting at 6 weeks is efficacious. Costs must be looked at against competing priorities

1. Introduction

Background

A pilot project to introduce Hepatitis-B Vaccine in 15 selected cities and 32 districts in 17 States of the country was launched in 1996 (Dasgupta 2002 ). This was done “in order to study the impact of administration (of hepatitis B vaccine) ”[ See answers to Parliamentary questions Appendix 7]

The pilot project was estimated to cost Rs.27.19 crores (out of which vaccines and auto-destruct AD syringes cost Rs.23.89 crores), and was funded by the Global Alliance on Vaccines and Immunization (GAVI).(Answer by Minister in RAJYA SABHA STARRED QUESTION NO 408 12.08.2002 Appendix 7)

In response to an earlier question the minister has said “Hepatitis B vaccination has not been included under the National Immunization Program as the estimated cost will be around Rs. 525 crores per annum and the measure if initiated will have to be continued indefinitely to cover all children born in the country with 3 doses. Availability of funds to sustain this over such a long period cannot be assured” (RAJYA SABHA UNSTARRED QUESTION NO 3428 17.07.1998 Appendix 7)

On September 6, 2005 the Minister for Health Dr A Ramadoss said the pilot project was highly effective and the vaccine was to be brought under the national immunization program. The vaccine is to be administered with DPT at the 6th 10th and 14th week of life. (Kounteya Sinha. Hepatitis B threat eclipses AIDS. Times of India New Delhi)

The National President of the IMA Dr Sundipo Roy set up a committee under the chairmanship of Prof S K Mittal to look at the issues involved. The committee met on 19 October 2005 and again on 18/1/06. It was decided to hold a national level consultation on 14/5/06 to discuss the issues related to Hepatitis B immunization in India. It was decided that prior to this, the sub committee must draft a White Paper that was a systematic review of literature to act as a position document.

The issues to be addressed in the White Paper

The problem

The magnitude of the problem of Hepatitis B in India.

a) Meta-analysis of all papers on prevalence of Hepatitis B
b) Understanding death rate from HCC and how the figure is arrived at

The costs of the solution

a) What will it cost? (Studies looking at cost of universal immunization)

Evidence of the success of the pilot project

Collate the evidence about the success of the project:

• Proportion of newborns in the pilot cities who received 3 doses of hepatitis B vaccine
• Carrier rate of Hepatitis B in children under 5 years of age, in cities covered under the pilot project, compared to carrier rate before the introduction of the pilot project
• Carrier rate among children who have not received birth dose compared to those who got the birth dose

Evidence in international literature of efficacy of a 6, 10, 14 week immunization strategy.

Meeting of Experts

A meeting of experts would be arranged by the IMA. The experts would be invited to contribute their own published data and that of others, to supplement the White Paper

The experts to be invited include:

The India Advisory Expert Group
Indian Academy of Pediatrics
WHO
UNICEF
Ministry of Health, (MOH) Government of India (GOI)
Researchers in the field

Methods adopted for the Systematic Review

In 2001 Lodha et al published a systematic review of Hepatitis B in India. A literature search was done for additional papers form 1999 onwards (assuming a publication delay of 18 months) up to January 2006 and incorporated. Other studies from the correspondence to Lodha’s article were also incorporated.

Search strategy and outcome

Primary sources

Medline via Pubmed

Search terms included “hepatitis b” [MeSH Terms] OR Hepatitis B[Text Word]) AND (“india” [MeSH Terms] OR India[Text Word])) AND (“1999”[PDAT] : “3000”[PDAT]. (Search date 19/1/06) yielded 272 hits. Titles and abstracts identified by electronic searches were examined independently by 2 researchers on screen to select potentially relevant studies that could provide answers to any of the subjects of interest enlisted above. Differences were resolved by consensus. Full text paper was obtained where ever possible. The reference list of these papers was examined for other papers of interest.

Secondary sources

Best bet.

Best bet search (http;//www.best bets . org/cgi-bin/browse.pl)
Search term: ‘Hepatitis.’ There were 2 articles neither of which were relevant

Cochrane collaboration (http://www.cochrane .de/cc_bin/)

Search term: ‘Hepatitis B’. 96 hits but none were relevant

Parliament question answers

For information available to the Government of India

2. Point Prevalence of Hepatitis B in India

Meta-analysis of all papers on prevalence of Hepatitis B

Exclusion criteria

We excluded studies from the following special groups: Sexually transmitted disease clinics, Thalassaemia clinics, professional blood donors, sex workers, samples from patients undergoing dialysis, and studies from hospital care staff, (as we assumed these were high risk groups.)

Inclusion

Studies from voluntary blood donors, replacement donors and antenatal women and the community we included.

Data extraction and data analysis

Analysis was done grouping patient in various grouping categories. We examined disease carrier rate in different geographic areas.

Lodha et al (2001) pointed out that when the estimated prevalence of a disease is low, there is need to calculate the error due to ‘misclassification errors’ caused by the false positives and false negatives (due to less than 100% specificity and sensitivity of the test used). For example in a hypothetical situation where the prevalence of a disease is zero, a test that has a specificity and sensitivity of 98% will show 2 positives in 100 tests and both would be false positives. Therefore such a test is not very useful to test prevalence, if the ‘true prevalence is less than 2%. The true prevalence can be found using the formula of Tu et al 1992.

True prevalence = [Estimated prevalence – (1 – specificity)]/[Sensitivity – (1 – specificity)]

Meta-analysis and Sensitivity Testing

All studies reviewed by Lodha and articles published till January 2006 were included. Studies which do not give details of the test used or where the specificity/ sensitivity of the test used are not known were excluded. If the prevalence detected in the study was very low (and it is less than the numerical value of 1-sensititivty of the test performed) the prevalence is considered as zero. However sensitivity analysis was performed and all studies were included as if the specificity and sensitivity of the tests were 100%/100%.

In the first stage, the incidence with its 95% confidence intervals were calculated for each individual study. In the second stage of meta-analysis, an overall incidence was calculated as a weighted average of individual summary statistics. Weights are calculated by a method due to DerSimonian & Laird. We used a random effects model. The results were displayed as a forest plot. (Figure 1)

Two features stand out in the forest plot.

1. The forest plot shows two distinct groups. The prevalence of Hepatitis B among tribal peoples was distinctly different from that of others. Meta-analysis has therefore to be done separately in the two groups.

2. There is no uniformity in the choice of sample sizes in various studies. It has been pointed out that the denominator considered in meta-analysis is the sample size rather than the population size from where the sample is drawn and this can bias the conclusions drawn, in favor of larger studies especially where the population represented is small. (Large sample sizes from small populations get undue weightage). It has been suggested that the sample prevalence must be seen against the size of the population of the area rather than the sample size studied. (Sreenivas 2005)

We have used this concept to further refine the meta-analysis by examining the studies in each state. A meta-analysis of the data from each state was used to arrive at the prevalence of hepatitis B in that state. Using the proportion of the population in each state to the total population (as per 2001 Census) as respective weights, the pooled prevalence in each state was meta-analyzed to find the overall prevalence for the country. We have examined the tribal population separately.

Results

Forest plot

The forest plot of the different studies is depicted below


It is apparent that there are two cluster groups and that tribal groups have a much higher prevalence compared to the others. The 2 groups are analyzed separately.

True prevalence

The true prevalence in the non-tribals is 2.13 (95% CI 1.83-2.46) [Appendix 1]
True prevalence among tribals is 19.45 (CI 15.35–23.55) [Appendix 2]  

Sensitivity testing

For sensitivity testing we assumed that all the tests performed, had 100% specificity and 100% sensitivity. No papers were excluded in this analysis. The prevalence on meta-analysis among non-tribal people was 2.71 (CI 2.45-2.97) [Appendix 3] The prevalence among tribal poplations was 20.25 (CI 16.28 – 24.22) [Appendix 4]


Meta analysis by state

Meta analysis was done analyzing the data from states separately.

These results are shown in the table below [Forest plots in Appendix 5]

COMBINED TRUE PREVALENCE FOR THE COUNTRY BASED ON EACH STATE”S WEIGHT (Excluding Tribal Pop)
State

ES

[95% Conf.    Interval]

% Weight

Andhra Pradesh (2)
Tamil Nadu (3)
Delhi (12)
Rajastan (3)
West Bengal (1)
Uttar Pradesh (5)
Punj+Harya+Chandi(5)
Karnataka (2)
Maharastra (4)
Gujarat (1)
Himachal Pradesh (1)

3.353
4.356
1.733
2.256
2.134
3.135
0.914
4.526
3.027
0.579
0.615

1.465
1.714
1.376
1.451
1.811
1.384
0.331
1.674
0.590
0.018
0.186

5.242
6.998
2.090
3.060
2.458
4.886
1.497
7.379
5.465
1.141
1.044

10.76
8.81
1.96
7.97
11.31
23.47
6.55
7.46
13.68
7.16
0.86

* pooled ES

2.794

2.139

3.450

100.00


Meta analysis by state using population weights

Large samples taken from small populations can unfairly bias the results of a meta-analysis (Sreenivas 2005) When each state was given weights in accordance with the population of the state rather than weights according to sample size, the overall mean prevalence worked out to be 3.26 (CI 2.63-3.90) The forest plot is shown in Appendix 6

Bottom line

Tribals in MP and the Andamans require special attention because they have a very high prevalence rate of HBV. The prevalence in these groups is approximately 10 times higher than that among non-tribal populations

The point prevalences of hepatitis B among non-tribals is 2.1% Chronic carrier state is diagnosed when a person is HBsAg positive on two occasions, 6 months apart. The chronic carrier rate is approximately 80% of the point prevalence (Phadke 2002). The chronic carrier rate therefore is estimated at a.6%

3. Hepatocellular carcinoma and Hepatitis B

Importance of knowing incidence of HCC due to HBV

The majority of hepatitis B carriers go through life unaware of their HBsAg status and unaffected by it. A small minority develops fulminent hepatic failure but this is a miniscule number (Aggarwal et al 2003). Some develop chronic active hepatitis, cirrhosis liver and from there go on to develop hepatocellular carcinoma (HCC). In India, in the absence of a surveillance system to track chronic liver disease, the incidence of hepatocellular carcinoma (due to hepatitis B) is a surrogate measure of the magnitude of the problem of chronic liver disease caused by the virus. The consensus statement of the Indian Association for Study of the Liver (INASL) used deaths from HCC as denominator when looking at cost per life saved and this is in keeping with publications from other parts of the world.

Data on HCC from the ICMR

The INASL consensus statement asserts that 184,000 die from HCC due to HBV each year. The Cancer Registry maintained by the Indian Council of Medical Research (ICMR) suggests that 5000 die of HCC due to hepatitis B in India each year. This registry records all deaths from cancer in well defined areas and looks at liver cancer as a proportion of deaths from all cancers. This data is available for each year from 1982. To avoid prolixity, only the data for the year 1999-2000 is presented. The inset discusses the detailed methodology used for purposes of the registry.

As HCC is looked as a proportion of all deaths from cancer, unless there is reason to feel that HCC notoriously mimics non-cancer disease, there is little reason for underreporting HCC as a portion of all cancers. A publication of the WHO (Prevention of Hepatitis B in India – an overview) suggests that the ICMR data was not available to the authors (of the WHO publication,) for analysis, [“articles not available for review”] and so we have reproduced details available from ICMR publications and from the ICMR web site.

Analysis shows that HCC forms 1.6% of all cancers in the country. Approximately 773,000 deaths in the country are due to cancer (Dhir et al 1998). Since mortality rates in HCC are almost the same as incidence rates, 11000 deaths in the country are due to HCC and of that 5000 are due to hepatitis B (Dhir et al 1998).

There have been attempts to use iterative mathematical models like the Markov model employing values for transition states from other countries but such studies have not been included here as they reflect the mortality in the countries from where the transition state data has been extracted.

It is interesting the INASL consensus statement which asserts that 184,000 die from HCC uses the ICMR figure of 5000 deaths for its cost calculation.

There have been attempts to use iterative mathematical models like the Markov model employing values for transition states from other countries but such studies have not been included here as they reflect the mortality in the countries from where the transition state data has been extracted.

It is interesting the INASL consensus statement which asserts that 184,000 die from HCC uses the ICMR figure of 5000 deaths for its cost calculation

INSET 1

Introduction to the Cancer Registry of India

The ICMR initiated the National Cancer Registry Program (NCRP) in 1981 and commenced a network of cancer registries across the country that started functioning from January 1982 with the objectives of;

1) Generating reliable data on the magnitude and patterns of cancer.
2) Undertaking epidemiological research.
3) Providing database for developing appropriate strategy to aid the national cancer control program.
4) Developing human response in cancer registration.

Data collection commenced from January 1982 in population based cancer registry (PBCR) at Bangalore, Chennai, Mumbai, and also in hospital based cancer registries (HBCR) at Chandigarh, Dibrugarh, Thiruvananthpuram. In order to extend the assessment, HBCR were also started at Bangalore, Chennai and Mumbai in 1984. From 1986, 2 more urban PBCR were started in Bhopal and Delhi, and for the first time a population based rural cancer registry (PBRCR) was started in 1987 in Barshi (Maharashtra).

To ensure uniformity in data collected by different registries, code manuals separately for HBCR’s were prepared, these code manuals are used for data from 1 January 1986. Cancer registrations in India is an active process; staff of registries visit hospitals on routine basis and scrutinize the records in various departments that include pathology, radiology, radiotherapy, in-patient and OPD to elicit the desired information. Coding of the disease is done according to the international classification of diseases (WHO –ICD 10).

INSET 2
AREA COVERED CANCER REGISTER AND POPULATION AT RISK ( 1999-2000)

REGISTRY

AREA(Sq. km)

MALE

FEMALE

TOTAL POPULATION

BANGALORE 365.7 2905880 2629271

5535151

BARSHI 3713 260385 242201 502786
BHOPAL 284 751722 674409 1426131
CHENNAI 170 2140395 2030344 4170739
DELHI 685 6697777 5513821 12211598
MUMBAI 693 6436794 5226942 11663736
INSET 3
TOTAL NO OF CANCER CASES REGISTERED ( 99-2000)

REGISTRY

MALE

FEMALE

TOTAL CASES

BANGALORE 3495 4083

7578

BARSHI 202 222 424
BHOPAL 952 847 1799
CHENNAI 3690 4182 8142
DELHI 9177 9057 18234
MUMBAI 8880 8701 8701
Total 26666 27092 53578
INSET 4
INCIDENCE OF LIVER CANCERS AS PROPORTION (PERCENTAGE) OF ALL CANCERS.
YEAR BANGALORE M/F BARSHI M/F BHOPAL M/F DELHI M/F MUMBAI M/F CHENNAI M/F
1988 2.49/ 1.05 0.00/ 0.00 3.16/ 1.29 1.93 / 1.44 2.68/ 1.42 3.09/ 0.49
1989 3.00/ 0.85 4.44/ 0.00 1.77/ 0.82 1.74 / 0.78 2.43/ 1.41 1.52 / 0.47
1990-1996 2.74/ 1.00 4.08/ 0.78 2.01/ 1.07 1.77/ 0.87 2.76/ 1.31 2.23/ 0.65
1997-1998 2.73/ 1.07 10.36/ 0.47 2.3/ 1.03 1.60/ 0.75 3.97/ 1.54 2.79/0.67
1999 3.79/ 0.98 7.61/ 0.89 2.15/ 1.70 1.86/ 0.67 3.48/ 1.76 2.63/ 1.06
2000 3.66/ 1.59 4.55/ 0.91 2.46/ 1.83 2.10/ 1.40 3.86/ 2.07 2.57/ 0.67


Bottom line

The data from the cancer registry seems robust. HCC is an uncommon cancer in India. If reports of deaths from cancer in the registry areas were to double, the burden of HCC due to HBV would rise to 10,000/year

4. Studies looking at national cost and benefits of immunization

Many authors have attempted to evaluate the costs of including Hepatitis B in the EPI. The conclusions drawn depend on the costs attributed to various inputs. These have been tabulated below

COSTS

Vaccine cost US$* Vaccine delivery US $ Total cost US $ per dose Birth dose costs
Aggarwal and Naik 1994 1.00 0.43 Costing by assumption 1.43 Not included
Aggarwal and Naik 1999 0.75 0.33 Costing by assumption 1.08 Not included
Prakash et al 1998 0.75 0.19 Costing by assumption 0.84 Not included
Miller and Kane 2000 0.50 0.19 Costing by assumption 0.69 Not included
Aggarwal et al 2003 0.50 0.50 Costing by assumption 1.00 Not included
Sahni et al 2004 Birth dose 4.00. Costing based on community trial.
Others doses given with DPT assumed at no extra cost.
1.30 for administering the vaccine per dose. Birth dose costs Included.
Cost of delivery of 2nd and 3rd dose not added. At $0.19 for 2nd and 3rd doses, it is $ 1.46 per dose
INASL 2000 [Clarification in Sarin 2001 Aggarwal & Sarin 2001** Sarin 2002] 0.40 1.00 1.40 Not explicitly stated.
Government of India 1.50 Birth dose costs
Vaccine cost US$* Vaccine delivery US $ Total cost US $ per dose Assumptions not known
* 1US$ = Rupees (Rs) 45
**Aggarwal & Sarin 2001 INASL cost of vaccine Rs 1350 million and delivery of vaccine Rs. 3650 million (Total Rs 5000 million)


The Government of India reckons it will cost Rs 525 crores per year

Given that 75million doses are required by the birth cohort each year, this works out at Rs 70/dose
Or $1.50/dose ($1 = Rs 45).

Cost without birth dose

Aggarwal et al’s (1979) cost estimation does not include the birth dose and is projected to cost Rs 337.5 crores
 
Miller and Kane (2000) have estimated cost of vaccine at $0.50 and delivery of vaccine at $ 0.19 without the birth dose. If we use costs estimated by Miller ( $0.70/dose) this will half the government estimate to Rs 250 crores

Cost including birth dose

The community based study by Sahni et al suggests that delivery of the first dose within 48 hours of delivery will cost $4 for the first dose. Even assuming that delivery of the second and third doses with DPT does not add any additional expense, the cost of delivery averages to $1.30 per dose.

If cost of delivery of 2nd and 3rd dose were added at $0.19/ dose, it averages to $ 1.46 per dose for delivery of vaccine alone. After adding the cost of vaccine at $ 0.50/dose the total cost can reasonably be expected to be Rs 675 crores.

Even if vaccine prices come down to zero, the cost of the program that includes the birth dose will be Rs 500 crores.

Bottom line on Costs

The GOI projection of yearly cost of Rs 525 crores seems reasonable in the light of the projections of most authors.

Economies of scale may push down the cost price of the vaccine. However even if the price of the vaccine comes down to zero, program implementation costs will be a big constraint.

Benefits

Benefits in terms of lives saved are used as the denominator, to calculate the cost per life saved and from that, the cost per life year saved is computed.

Studies have made serious errors in this by over estimating benefits. The error has been acknowledged by Miller (Miller 2004)

The INSAL consensus use ICMR data that suggests that 5000 lives are saved each year, for their cost analysis.

The synthesis of costs and benefits

Author Number of deaths prevented Cost/ life saved Undiscounted Cost/ life saved Discounted 3% Cost/Life year saved Undiscounted Cost/Life year saved Discounted 3% Birth dose Cost included
INASL 5000 Rs. 270,000 Not known
Miller et al 2000 193,000 Rs. 14,040 ($312) Rs. 53010 ($1178) Rs. 540
($12)
Rs. 2970 ($66) Not included
Miller after correction 5000 Rs. 541,944 Rs. 2046,186 Rs. 20844 Rs. 114,642 Not Included
Sahni et al 5000 Rs. 1000,000 Rs. 48,540 Rs. 262,120 Included


Bottom line

Tyagi et al 2003 suggest that an intervention that costs more per life year saved, than the per capita GNP of the country is not cost beneficial. The per capita GNP in India is about Rs 20250
By this reckoning, interventions that cost more than Rs 20250 per life year saved (after discounting) are not cost beneficial for India.

The cost of the hepatitis B program is 5 times (without the birth dose) to 10 times (with birth dose) the percapita GNP, per life year saved. The program is therefore too costly and there are no commensurate benefits.

5. Evidence of the success of the pilot project

GAVI funded the pilot study in India and it was a success we are told (statement of minister of Health quoted by times of India). We looked for evidence from evaluations of the pilot study.

Carrier rate in pilot area (against historic controls)

What is the carrier rate among children under 5 years in cities where the pilot was conducted compared to the carrier rate before the introduction of this prophylaxis? Only one paper from tribals in Andamans who were vaccinated at birth( Murhekar 2004)

Carrier rate in those immunised starting at 6 weeks

What is the carrier rate among children vaccinated at 6, 10 and 14 weeks in the pilot area compared to those who received the birth dose? This would help answer the question about the importance of the first dose within 48 hours of birth.

There is no data

Carrier rate in those immunized (compared to those not immunized)

This would be more useful than using historic controls

There is no data

Vaccine uptake in the pilot project areas

We have one study from East Delhi that says that the coverage with hepatitis B was 14% - only marginally more than the baseline 9% before the vaccine was made available free of cost by the GAVI (Sokhey et al 2001)

Another study from Delhi found coverage of 19 to 21.6% (Dasgupta R et al 2002.)

What else is known from the pilot study?

We know 270 million rupees have been spent. This is perhaps the only real mark of success.

Bottom line

There is no evidence that the pilot project was a success.

6. Evidence in international literature of efficacy of a 6, 10, 14 week immunization strategy

A systematic search was made of international literature to see if there was evidence that the 6,10, 14 week schedule of immunization or any similar schedule has been utilized and found to be effective in reducing HBsAg prevalence.

Search strategy

Pubmed ("hepatitis b"[MeSH Terms] OR hepatitis b[Text Word]) AND ("epidemiology"[Subheading] OR "prevalence"[MeSH Terms] OR prevalence[Text Word]) AND after[All Fields] AND (immunization[Text Word] OR immunisation[Text Word] OR "immunization"[MeSH Terms]) 324 hits.

Results

Although papers from Taiwan(Cheng 2003, Ni YH 2001, Kao 2001, Lin 2002, Lee 200)
China (Gong 2003) Iran(Zali 2005) USA (Mahony 2003) Italy (DaVilla 1998, Zanetti 2001 Mele 2002) Thailand (Poovorawan 2000) Andamans India ( Murhekar 2004) Nigeria (Odusanya et al 2005) showed reduction in carrier rate after universal immunization starting at birth, we found no papers where immunization starting at 6 weeks has been proven efficacious

Bottom line

There are no studies from anywhere in the world where the 6, 10, 14 week schedule of immunization has been employed and shown to be useful.

7. Conclusions

1. Systematic review suggests that prevalence of Hepatitis B in India among non-tribals is 2.13% (CI 1.83 – 2.46). The incidence among tribals is significantly higher at 19.455%(CI 15.35-23.55).
The data regarding tribals must be seen separately so that this vulnerable group gets the attention needed.
2. The data of the ICMR cancer registry, which estimates 5000 deaths from HCC due to HBV seems robust.
3. There is no data collected from the pilot program to suggest that universal immunization with Hepatitis B is feasible, affordable or efficacious.
4. There is no evidence in world literature to suggest that immunization starting at 6 weeks can bring down the prevalence of hepatitis B.
5. The program is expected to cost Rs 500 crores. Benefits have to be discounted as they will accrue about 40 years in the future. If vaccination is to start at birth most of this allocation will get spent on delivery of the first dose of the vaccine within 48 hours of birth

The INASL had recommended urgent need for data on benefits in spite of missing the birth dose. (INASL 2000) The information can be derived from studies in the pilot area

Scaling up from a donor-funded pilot study costing Rs 27 crores, to universal immunization which is to cost the Indian exchequer Rs 500 crores yearly, seems difficult to justify in the absence of an evaluation of the pilot project

Recommendation for research

An evaluation of the pilot study will cost a very small fraction of the Rs 500 crores needed each year for universal immunization.

Immunization coverage with hepatitis B must be studied in children born in the pilot areas.

Carrier rates among those who have not received any hepatitis B vaccine must be compared with carriers among those that received the vaccine at birth and those that received it, starting at six weeks.

Bottom line

The study in the pilot areas would cost a fraction of the yearly expenditure of embarking on the program of universal immunization. Embarking on this program without collecting data that is easily available from the pilot study would be irresponsible and difficult to defend.

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Appendix
Appendix 1 True prevalence Non Tribal Populations
Study ES [95% Conf.       Interval] % Weight
Nayak NC (1987) 2.930 2.573 3.287a 3.75
Biswas SC (1989) 1.462 0.718 2.206 3.17
Werner GT (1989) 2.548 0.974 4.122 1.87
Singhvi A (1990) 2.009 1.863 2.155 3.92
Elavia AJ (1991) 1.182 0.975 1.390 3.89
Panda SK (1991) 1.428 1.174 1.681 3.85
Tandon BN (1991) 1.300 0.591 2.008 3.23
Thakur TJ (1991) 0.615 0.186 1.044 3.66
Satoskar (1992) 3.887 3.207 4.567 3.28
Irshad M (1994) 1.763 1.583 1.944 3.90
Nandi J (1994) 5.580 0.940 10.221 0.37
Chodhary N (1995) 1.721 0.280 3.161 2.05
Sumathy S (1995) 6.608 4.493 8.722 1.31
Sharma R (1996) 9.421 4.852 13.991 0.38
Nanu A (1997) 1.076 1.020 1.132 3.96
Prakash C (1998) 8.757 7.095 10.418 1.76
Ganju SA (2000) 2.673 0.437 4.908 1.22
Abass Faud (2001) 0.164 0.069 0.260 3.95
Ahmad B (2001) 1.595 0.797 2.393 3.08
Garg s (2001) 2.612 2.467 2.756 3.93
Kaur H (2001) 0.857 0.784 0.930 3.95
Singh J (2001) 3.345 2.111 4.579 2.35
Singh J (2001) 2.427 1.316 3.538 2.54
Kaur R (2002) 6.451 3.553 9.349 0.83
Vinod Kumar CS (2002) 6.320 3.401 9.238 0.82
Chandra M (2003) 4.356 3.015 5.696 2.19
Singh H (2003) 1.215 0.420 2.010 3.08
Qamer S (2004) 3.528 1.842 5.214 1.74
Sahni Mohit (2004) 1.391 0.660 2.121 3.19
Sharma RR (2004) 0.151 0.135 0.167 3.96
Singh B (2004) 0.927 0.875 0.979 3.96
Bhagyalaxmi A (2005) 0.579 0.018 1.141 3.47
Chakravarthi (2005) 3.429 1.646 5.212 1.63
Chakravarthi (2005) 1.412 0.256 2.568 2.47
Chowdhury A (2005) 2.134 1.811 2.458 3.78
Kurien T (2005) 4.896 3.946 5.846 2.81
D+L pooled ES 2.131 1.834 2.427 100.00
Heterogeneity chi-squared = 4594.22 (d.f. = 36) p = 0.000
I-squared (variation in ES attributable to heterogeneity) = 99.2%/
Estimate of between-study variance Tau-squared = 0.5767

Test of ES=0 : z= 14.09 p = 0.000

Appendix 2 True prevalence in tribal populations
  Study                        | ES [95% Conf. Interval] % Weight
------------------------------------------------------------------------------
Joshi SH (1990)           | 14.954  13.026   16.883   16.86
Murvekar MV (2002) | 21.543  18.837   24.248    16.27
Murvekar MV (2002) | 22.682   20.255   25.109   16.50
Murvekar MV (2002) | 37.305   21.722   52.888     4.97
Murvekar MV (2002) | 30.443   18.601   42.286     7.12
Murvekar MV (2002) | 2.878    -3.428     9.185     12.39
Murvekar MV (2003) | 18.053   8.630     27.477     9.10
Murvekar MV (2004) | 21.826   19.785   23.867   16.78
------------------------------------------------------------------------------
D+L pooled ES           | 19.455    15.351   23.558 100.00
------------------------------------------------------------------------------

Appendix 3 Sensitivity Testing: Prevalence among Non-Tribals assuming complete sensitivity and specificity
 Study                                                  | ES      [95% Conf. Interval] % Weight
------------------------------------------------------------------------------------------------------
Khatri JV (1980)                                  | 0.627   0.194    1.060                    2.68
Nayak NC (1987)                                | 3.755   3.353    4.157                    2.71
Biswas SC (1989)                                 | 2.300   1.371    3.229                    2.11
Makroo RN (1989)                               | 1.114   0.882    1.345                    2.83
Werner GT (1989)                                | 3.377   1.572    5.181                    1.21
Singhvi A (1990)                                  | 2.842   2.669    3.015                    2.86
Elavia AJ (1991)                                   | 2.022   1.752    2.293                    2.81
Panda SK (1991)                                  | 2.265   1.948    2.583                    2.78
Tandon BN (1991)                               | 2.138   1.234    3.043                    2.14
Thakur TJ (1991)                                  | 2.590   1.718    3.463                    2.18
Gupta L (1992)                                     | 2.482   1.851    3.113                    2.47
Satoskar (1992)                                     | 4.704   3.959    5.448                   2.34
Irshad M (1994)                                    | 2.598   2.380    2.817                   2.84
Nandi J (1994)                                      | 6.383   1.441   11.325                   0.25
Chodhary N (1995)                              | 2.556   0.808     4.304                   1.25
Sumathy S (1995)                                 | 6.981   4.812      9.151                  0.96
Kaur U (1996)                                       | 2.899   1.990      3.807                  2.14
Kaur U (1996)                                      | 2.934    1.778      4.090                  1.84
Sharma R (1996)                                  | 10.191  5.459     14.923                 0.27
Nanu A (1997)                                     | 1.917    1.843       1.991                 2.89
Nijhawan S (1997)                               | 2.100    1.993       2.207                 2.88
Sharma R (1997)                                  | 5.096    1.656       8.535                 0.47
Prakash C (1998)                                 | 9.532    7.806      11.258                1.27
Mohite JB (1999)                                  | 2.111    1.238        2.984                2.18
Chandrasekharan S (2000)                 | 4.123    3.209        5.037                2.13
Ganju SA (2000)                                  | 3.500    0.953        6.047                0.76
Abass Faud (2001)                               | 1.013    0.777        1.249                2.83
Ahmad B (2001)                                   | 2.431    1.450       3.413                 2.05
Garg s (2001)                                        | 3.439    3.274       3.604                 2.86
Kaur H (2001)                                       | 1.700   1.597       1.802                 2.88
Singh J (2001)                                        | 4.167   2.796       5.538                 1.60
Singh J (2001)                                        | 3.256   1.975       4.538                 1.70
Hazra Sc (2002)                                     | 4.000   0.159        7.841                0.39
Joshi RM (2002)                                     | 2.011   1.822        2.200                2.85
Kaur R (2002)                                        | 7.246   4.188       10.305               0.58
Murvekar MV (2002)                            | 3.704   -3.420      10.827               0.13
Vinod Kumar CS (2002                        | 7.116    4.032       10.200              0.57
Chandra M (2003)                                | 5.169    3.714         6.623              1.52
Singh H (2003)                                      | 2.055    1.026         3.084              1.99
Gupta N (2004)                                     | 0.658    0.583         0.734              2.89
MahaLakshmi B (2004)                        | 3.520    1.876         5.163              1.34
Mathew Raji (2004)                              | 0.820    0.598         1.042              2.84
Qamer S (2004)                                     | 4.348    2.484         6.211              1.16
Sahni Mohit (2004)                               | 2.229    1.308         3.150              2.12
Sharma RR (2004)                                 | 1.000   0.960          1.040              2.90
Singh B (2004)                                       | 1.769    1.697         1.841              2.89
Benerjee A (2005)                                  | 3.750    1.888         5.612              1.16
Bhagyalaxmi A (2005)                          | 1.425     0.548        2.301              2.18
Chakravarthi (2005)                             | 4.250     2.273        6.227              1.08
Chakravarthi (2005)                             | 2.250     0.797        3.703              1.52
Chowdhury A (2005)                           | 2.966     2.586        3.346              2.73
Kurien T (2005)                                     | 5.704     4.683        6.725              2.00
------------------------------------------------------------------------------------------------------
D+L pooled ES                                       | 2.712     2.452        2.971          100.00

Appendix 4:Prevalence in Tribal Populations assuming tests were 100% specific and 100% sensitive
 Study                                      | ES        [95% Conf.   Interval]      % Weight
-----------------------------------------------------------------------------------------------------
Joshi SH (1990)                       | 15.677  13.711            17.643          17.32
Murvekar MV (2002)             | 22.210  19.474            24.945          16.65
Murvekar MV (2002)             | 23.339  20.888            25.790          16.92
Murvekar MV (2002)             | 37.838  22.211            53.465            4.75
Murvekar MV (2002)             | 31.034  19.128            42.941            6.88
Murvekar MV (2002)             | 3.704     -3.420            10.827          11.42
Murvekar MV (2003)             | 18.750    9.188            28.312            8.82
Murvekar MV (2004)             | 22.490  20.428            24.553          17.24
-----------------------------------------------------------------------------------------------------
D+L pooled ES | 20.249 16.281 24.216 100.00

Appendix 5: Meta Analysis of True Prevalence by State (Using Weights of sample size)
 Region                                           | N(total)    sum(total)   sum(positive)
----------------------------------------------------------------------------------------------------
Andhra Pradesh                            |  2             1627                    70
Tamil Nadu                                    |  3           37906                1156
Delhi                                               | 13        310172                6116
Rajasthan                                       |   3          48103                1645
West Bengal                                    |  1            7653                  227
Uttar Pradesh                                 |  5            1817                    67
Punjab & Haryana                         |  4        297626                3423
Karnataka                                       |  2            1083                    53
Maharastra                                     |  3          13631                  363
Gujarat                                            |  1              702                    10
Andamans- Tribals                         |  7            3791                  863
Himachal                                         |  1            1274                    33
Madhya Pradesh                             |  1            1314                  206
----------------------------------------------------------------------------------------------------

Study                                            | ES    [95% Conf. Interval]      % Weight
----------------------------------------------------------------------------------------------------
AP                                                 | 3.353   1.465         5.242               10.76
TN                                                 | 4.356   1.714         6.998                 8.81
Delhi                                             | 1.733    1.376        2.090                 1.96
Rajastan                                        | 2.256    1.451        3.060                7.97
WB                                                | 2.134    1.811        2.458               11.31
UP                                                 | 3.135    1.384        4.886               23.47
Punj+Haryana                              | 0.914    0.331        1.497                6.55
Karnataka                                     | 4.526    1.674        7.379                7.46
Maharasra                                    | 3.027    0.590        5.465              13.68
Gujarat                                          | 0.579    0.018        1.141               7.16
HP                                                 | 0.615     0.186       1.044                0.86
----------------------------------------------------------------------------------------------------
* pooled ES                                   | 2.794      2.139       3.450            100.00

Appendix 6: Meta analysis after using population weights
COMBINED TRUE PREVALENCE FOR THE COUNTRY BASED ON EACH STATE”S WEIGHT (Including Tribal Pop)
Study                                       ES        [95% Conf. Interval]         % Weight

AP                                         3.353       1.465          5.242                 10.35
TN                                         4.356       1.714          6.998                   8.47
Delhi                                     1.733       1.376          2.090                   1.88
Rajastan                                2.256       1.451          3.060                  7.67
WB                                        2.134        1.811          2.458                10.88
UP                                         3.135        1.384          4.886                22.56
Punj+Haryana                      0.914       0.331           1.497                 6.30
Karnataka                             4.526       1.674           7.379                 7.18
Maharasra                            3.027        0.590           5.465               13.15
Gujarat                                  0.579       0.018            1.141                 6.88
Andaman-tribes                   20.318     16.039         24.598                0.00
HP                                           0.615       0.186           1.044                0.83
MP - Tribals                          14.954     13.026         16.883                3.85

* pooled ES                             3.264        2.629          3.898              100.00

Appendix 7: Answers to Parliamentary Questions

GOVERNMENT OF INDIA
MINISTRY OF HEALTH AND FAMILY WELFARE
RAJYA SABHA
UNSTARRED QUESTION NO 3428
TO BE ANSWERED ON 17.07.1998
INCLUSION OF HEPATITIS B VACCINE IN THE NATIONAL IMMUNISATION PROGRAMME .

3428. DR. D. MASTHAN

Will the Minister of HEALTH AND FAMILY WELFARE be pleased to state:-

(a) how many people/children have died due to Hepatitis-B virus during the last three years in the country;

(b) whether Government will include Hepatitis-B vaccine in the National Immunisation Programme to eradicate this killer virus; and

(c) if answer to part

(b) of the question be in the negative, the reasons therefor? ANSWER

ANSWER

MINISTER OF STATE OF THE MINISTRY OF HEALTH AND FAMILY WELFARE (SHRI DALIT EZHILMALAI)

(a) No authentic data is available of the number of the deaths caused by Hepatitis-B infection alone. However, according to available data, the number of cases of viral Hepatitis (all types) during 1995 to 1997 (provisional) is as follows:-

Year           No. of Persons infected                 No. of persons died

1995                    98943                                              943
1996                    11795                                           4 801
1997                    89038                                              962

(b) and (c) Hepatitis B vaccination has not been included under the National Immunization Programme as the estimated cost will be around Rs. 525 crores per annum and the measure if initiated will have to be continued indefinitely to cover all children born in the country with 3 doses. Availability of funds to sustain this over such a long period cannot be assured.

In order to reduce the risk, however State Governments have been advised to provide vaccination to the concerned hospital workers.


MINISTRY OF HEALTH AND FAMILY WELFARE
MINISTRY OF 29
RAJYA SABHA
STARRED QUESTION NO 408
TO BE ANSWERED ON 12.08.2002

CHEAPER HEPATITIS B VACCINE .

408. SHRI BHAGATRAM MANHAR
        RAJU PARMAR

Will the Minister of HEALTH AND FAMILY WELFARE be pleased to state:-

(a) whether it is a fact that Hepatitis-B spreads very easily and one in every twenty Indians is already infected with this killer disease;

(b) if so, the steps Government have taken or propose to take for protection against this disease;

(c) whether cheap vaccines are available in the country for the poor; and

(d) if not, the steps being taken to procure Hepatitis-B vaccines at cheaper rates?

ANSWER

THE MINISTER OF STATE IN THE MINISTRY OF HEALTH AND FAMILY WELFARE (SHRI A. RAJA)

(a) to (d): A statement is laid on the table of the House.

STATEMENT REFERRED TO IN REPLY TO RAJYA SABHA STARRED QUESTION NO. 408 FOR 12.8.2002 ....

Hepatitis-B spreads through unsafe sex, unsafe blood transfusion, unsafe injections etc. and also from mother to child. Hepatitis-B is preventable by ensuring precautionary measures. Studies undertaken so far, indicate that about 3% to 5% of the population in the country is suffering from Hepatitis-B infection. The following measures have been taken to prevent infection of Hepatitis-B :- Central Government hospitals personnel at high risk are being immunized against Hepatitis-B. State Governments have also been advised to take similar steps. Guidelines have been issued for mandatory testing of blood in all blood banks. Promotion of safe sex under National AIDS Control Programme is advocated. Health awareness campaigns regarding the danger of using unsterile syringes and needles under National AIDS Control Programme are held. Guidelines have been issued to State Health Authorities for use of separate sterile syringes and needles for each injection. A pilot project to introduce Hepatitis-B Vaccine in 15 selected cities and 32 districts in 17 States of the country, which are high risk areas, in order to study the impact of administration has been launched. The pilot project is estimated to cost Rs.27.19 crores out of which vaccines and AD syringes cost Rs.23.89 crores, which will be funded by the Global Alliance on Vaccines and Immunization (GAVI).

Vaccines for Hepatitis-B is available in the country at affordable prices.