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Trends In Non-polio Acute Flaccid Paralysis Incidence In India

Authors:

Abstract

Background: Although the incidence of polio acute flaccid paralysis (AFP) is coming down in India, the non-polio AFP (NPAFP) rate has increased. Nationwide, the NPAFP rate is 13.7/100,000 where the expected rate is 1-2/100,000. We examined the correlates of NPAFP, to discern explanations for the increase.
Article ID: WMCPLS0035 ISSN 2051-0799
Trends In Non-polio Acute Flaccid Paralysis
Incidence In India
Corresponding Author:
Dr. V. Sreenivas,
Associate Professor, Department of Biostatistics, All India Institute of Medical Sciences, New Delhi , Department
of Bio-statistics, All India Institute of Medical Sciences, New Delhi 110029, 110029 - India
Submitting Author:
Dr. Jacob Puliyel,
Head of Pediatrics, Department of Pediatrics, St Stephens Hospital, St Stephens Hospital, Tis Hazari, Delhi
110054, 110054 - India
Submitted on:17-Jan-2014, 08:58:35 AM GMT
Accepted on:21-Jan-2014, 02:42:46 AM GMT
Article ID: WMCPLS0035
Article Type: Research articles
Article URL: http://webmedcentralplus.com/article_view/35
Subject Categories:PAEDIATRICS
Keywords:Acute flaccid paralysis, surveillance, vaccination, polio
How to cite the article:
Puliyel J, Vashisht N, Sreenivas V.Trends In Non-polio Acute Flaccid Paralysis Incidence In India.
WebmedCentral plus PAEDIATRICS 1970;-39(1):WMCPLS0035
Source(s) of Funding:
JP conceived the study and planned it with NV and VS. NV collected the data, VS did the statistical analysis with
NV, NV wrote the first draft of the paper that was revised by JP and VS. The final draft is approved by all the
authors. VS and JP are guarantors.
Competing Interests:
None
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Trends In Non-polio Acute Flaccid Paralysis
Incidence In India
Author(s): Puliyel J, Vashisht N, Sreenivas V
Abstract
Background: Although the incidence of polio acute
flaccid paralysis (AFP) is coming down in India, the
non-polio AFP (NPAFP) rate has increased.
Nationwide, the NPAFP rate is 13.7/100,000 where
the expected rate is 1-2/100,000. We examined the
correlates of NPAFP, to discern explanations for the
increase.
Methods: National Polio Surveillance data 2000-2012
was used. Differences between states and changes
over time were examined. Demographic factors and
polio programme parameters were assessed. Multiple
linear regression analysis adjusting for region/state,
literacy rate, female literacy rate, population density
and per-capita GDP was performed.
Results: NPAFP increased with the OPV doses used.
(R2=32.1%;P2=62.5). Per capita income of the state,
female literacy and overall literacy showed negative
correlation with NPAFP. This disappeared in a
multivariable analysis when the number of doses of
OPV was considered. On multiple regression analysis,
the number of OPV doses was the only factor that
showed a positive correlation with the NPAFP rate.
NPAFP in UP and Bihar decreased in 2012 coinciding
with a reduction in OPV administered.
Conclusion: Our observation showed positive
association between NPAFP and the number of OPV
doses. In 1994 the National Academy of Sciences,
Washington noted a causal relation between
Guillain-Barre syndrome and OPV. We hope our
findings will stimulate further work to bring down the
NPAFP incidence and if needed, to rationalize and
optimize the dose schedule of the OPV.
Key words: Acute flaccid paralysis, surveillance,
vaccination, polio
Introduction
Acute Flaccid Paralysis (AFP) surveillance helps
identify poliovirus circulation promptly and also
provides certification quality evidence that wild polio
transmission is not occurring. To qualify as AFP for
polio surveillance, there must be acute onset of focal
weakness or paralysis with reduced tone in the
absence of other obvious cause (like trauma) in
children under 15 years (1). The full list of causes of
non-polio AFP were reviewed and listed by Marx and
colleagues (2). Transient weakness (postictal
paralysis for example) is not included (3). In the
absence of wild polio transmission, the WHO
estimates that there is a background annual incidence
of at least 1 case of AFP per 100,000 children under
15 because of diseases like Guillain–Barré syndrome
(GBS). In other words, once polio is eradicated, it is
expected that the AFP rate (made up of polio and
non-polio AFP) would come down to 1 to 2 per
100,000 as there would only be non polio AFP left (4).
The surveillance performance of India has been
excellent, and the incidence of polio AFP is coming
down in the country (5). As a consequence the total
AFP rate (which includes polio and non-polio causes
of AFP) must come down with the non-polio AFP rate
remaining steady. Inexplicably however, the non-polio
AFP rate has shown a trend to increase. Nationally,
the non-polio AFP rate is 13.7 per 100,000 (2012 data)
where the acceptable rate is 1 to 2 per 100,000 (6). In
the state of Uttar Pradesh (UP) the non-polio AFP rate
is 24.6 per 100,000 and in Bihar this is 37 per 100,000
(2012 data) (5). It has been said that the increase in
AFP in recent years is the result of a deliberate effort
(that began in 2004) to intensify surveillance and
reporting in India (7). However, a surveillance program
no matter how good, can only record every case of
AFP, but it cannot exaggerate the numbers or explain
the 20 to 40 fold increase in the non-polio AFP rate,
as seen in the state of Bihar (assuming that the
natural non-polio AFP rate should lie between 1 to 2
per 100,000 as per internationally accepted norms)
(6). The lowest non-polio AFP rates are seen in the
states were polio was eliminated earliest. These are
the states which must have had the best
implementation of the polio control programme and the
best surveillance. If good surveillance was the reason
for the increase in non-polio AFP, it is paradoxical that
the well-performing states should have the lowest
non-polio AFP rates.
Follow-up of these cases of non-polio AFP is not done
routinely. However a fifth of these cases of non-polio
AFP in the state of Uttar Pradesh were followed-up
after 60 days, in 2005. 35.2% were found to have
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residual paralysis and 8.5% had died (total residual
paralysis or death 43.7%). (8) This suggests that the
pathology in children being registered as non-polio
AFP cannot be considered as trivial. There is thus
impelling reason to try and understand the underlying
causes for the surge in non-polio paralysis numbers.
The AFP rates are different in the various states and
Union Territories of India. In this study we examined
the factors that correlate with the non polio AFP rates
in the states, to discern possible explanations for the
increasing incidence of non-polio AFP. Data on AFP
rate from the National Polio Surveillance Programme
(NPSP) in India over the period 2000–2012 was used.
Differences between states and changes over time
with respect to non-polio AFP were examined.
Association with demographic factors and polio
programme parameters were assessed.
States reporting more wild polio cases are targeted for
increased vaccine coverage. For example it was
reported that during the year 2005, children under 5
years in UPand Bihar received on average 15 doses of
trivalent oral polio vaccine (tOPV), compared with 10
doses in the rest of India (9). Confounding is a
possibility. On cursory examination of the NPSP data it
appears that the states with the highest polio rates are
also the ones with higher non-polio AFP rates. It is
conceivable that the factors that result in higher polio
incidence in these states, also promote non-polio AFP.
Grassly and colleagues suggest that high population
densities and poor sanitation explain the persistence
of polio (9). We aimed to see whether various factors
like population density, literacy and poverty could
explain the non-polio AFP rate.
Matherials and methods
The data on AFP, polio and non-polio AFP and
number of polio rounds were examined in each state
in each year from 2000 to 2012. Data from the
National Polio Surveillance web site (5) was used. The
raw data, as extracted from the web site, has been
uploaded as supplementary file (and also available at
http://bit.ly/npsi_data). Data on numbers of polio
rounds during the years 2003 and 2012 was
incomplete and so figures for these years were not
included in the general analysis. However data from
2012 on polio rounds for some states were available
and they were used in analysis specific for those
states. When different areas within a state received
different numbers of doses, the arithmetic mean of
doses was taken as the representative dose for that
state. Normal linear regression analysis was carried
out, taking the non-polio AFP rate as the outcome
variable and the number of OPV doses as the
explanatory variable. Both these were treated as
continuous variables. Multiple linear regression
analysis was carried out to adjust for region/state,
literacy rate, female literacy rate and per capita GDP.
Pearson’s correlation coefficient of non-polio AFP rate
with the per capita income (10) and population density
(11) of each state and union territory were looked
into. According to Rosser and colleagues, sanitation
is closely linked to female literacy in a range of Asian
countries. (12) We could not find authentic data on
sanitation in the different states and hence we used
female literacy as a surrogate for social development
and also of the general level of sanitation and hygiene
in each state. Data on female literacy and overall
literacy was obtained from the Census of India (13).
We also included overall literacy because some
communities tend not send their girl children to school
and we expected overall literacy may have a positive
effect on the evolving social developments of the area,
which may not be reflected entirely and accurately by
female literacy in that area.
We explored whether any correlation exists between
the non-polio AFP rates and the number of doses of
polio vaccine used in the state in that year. Further, we
tried to look for cumulative effect by adding data on
vaccine doses from previous years.
Results
The non-polio AFP rate per 100,000 increased with
increased number of OPV doses during 2000-2011,
irrespective of time and region. Figure 1 shows the
trend of non-polio AFP with doses of OPV. As can be
seen, the relationship is curvilinear with a more steep
increase in non-polio AFP beyond 6 doses of OPV. To
demonstrate this association, the Pearson correlation
was calculated. This association is statistically highly
significant (R2= 32.1%; P)
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Figure 1: Trends in Non Polio AFP rate with
number of OPV doses
Looking at data up to 2012 from Uttar Pradesh and
Bihar, where the maximum doses of OPV were used,
the R2 was 51.9% (P < 0.001). Regression analysis
indicated that for an increase of one dose of OPV, the
non-polio AFP rate increased on the average by 3.7
per 100,000 populations under 15 (95% CI: 2.1-5.3).
The relation is shown in Figure 2. To examine the
trends over time we looked at the relationship of the
non-polio AFP rate each year to the number of doses
of OPV received in that year separately for UP and
Bihar. Figure 3 shows the non-polio AFP over the
years in the states of UP and Bihar alongside the 4
year cumulative OPV doses. The fall in NPAFP rate
for the first time in 2012 with a decrease in the OPV
doses is noted.
Figure 2: Trends in Non Polio AFP rate with
number of OPV doses in UP and Bihar
Figure 3: Yearly trend in non-polio AFP rate with 4
year cumulative polio doses in Bihar and UP
The figures on the Y axis represent number of
doses of polio and the non-polio AFP rate /100,000
children.
When the effect of cumulative doses over the previous
years was examined, the non-polio AFP rate in 2011
best correlated to the cumulative doses received in the
previous 4 years. Association (R2) of non-polio AFP
rate with OPV doses received in 2011 was 52.6%. It
increased to 56.9.6%, when we looked at AFP rate in
2011 related to total doses received in the years 2010
and 2011. Adding up dosesreceived in 2009 to that in
2010 and 2011 further increased the association (R2 =
54.4%) and adding up doses received between 2009
and 2011 the regression coefficient rose to 62.5. All
these correlations were highly significant (P < 0.001).
The association showed no further improvement with
addition in OPV doses from earlier years.
Per capita income of the state, female literacy and
overall literacy showed negative correlation with the
non-polio AFP (R2 = 4.1%, P < 0.001; R2 = 13.0%, P <
0.001; and R2 =12, P < 0.001 respectively).
Population density did not show any association with
the non-polio AFP (R2 = 0.0%, P = 0.91).
A multivariable model to adjust simultaneously the
influence of factors like overall literacy, female literacy
and per capita GDP, confirmed the significant positive
association between the number of OPV doses and
non-polio AFP rate. Per capita income, female literacy
and overall literacy did not show significant association
with non-polio AFP rate once we considered the
number of doses of OPV. After adjusting for these
factors, the average increase in the non-polio AFP rate
was 1.30 per 100,000 (P < 0.001, 95% CI: 1.09-1.51)
with each dose of OPV. The results of this multiple
regression analysis are presented in Table 1.
Table 1: Multivariate Regression Analysis
Discussion
Our results indicate that the incidence of non-polio
AFP was strongly associated with the number of OPV
doses delivered to the area. We also observed a dose
response relation with cumulative doses over the
years, which further strengthen the hypothetical
relationship between polio vaccine and non-polio AFP.
The cumulative dose received in the previous 4 years
related best to the non-polio AFP rate in 2011.
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Children over 5 are not vaccinated and the vaccine
naïve newborns are added to the pool each year and
this is perhaps the reason cumulative doses beyond 4
years did not improve the strength of association. The
fall in the NPAFP rate in Bihar and UP for the first time
in 2012, with a decrease in the number of OPV doses
delivered, is further corroborative evidence of a
causative association between OPV doses and the
NPAFP rate
A regression analysis reveals an association but does
not prove a causal role. Ecological fallacies must be
borne in mind meaning that correlation of aggregate
variables take into account cross sectional effects
which are not relevant at the individual level. The
likelihood of confounding also needs to be kept in
mind. Poor sanitation can cause spread of
entero-pathogens (like Campylobacter jejuni) which
cause non polio flaccid paralysis. The same sanitation
problem can result in increased polio in that area and
this will trigger more frequent polio immunization
rounds in the locality. Thus, a spurious relationship
between OPV doses and non-polio flaccid paralysis
may be inferred when poor sanitation is the real culprit
- the confounding variable – causing the non-polio
AFP.
Data from the WHO / UNICEF Joint Monitoring
Programme (JMP) for Water Supply and Sanitation,
suggests that states of Delhi and Kerala, with a female
literacy rate of 75% and 88% respectively have
achieved millennium development goals (MDGs) on
sanitation already, while Assam with 64% female
literacy and Arunachal with 55% female literacy will
achieve it in 10 years, and Madhya Pradesh and
Orissa with 50% and 51% female literacy respectively,
will achieve the MDG only in the next century. (14)
This further supports the observation that sanitation is
linked to female literacy in many Asian countries. (12)
In the absence of hard data on the number of
households with toilets for safe disposal of excreta and
free running water, we tried to remove the confounding
effect of poor sanitation, by using female literacy as a
surrogate for social development in the state and its
level of sanitation and hygiene. We did not find an
association of non-polio AFP rates with female literacy
in the multivariable analysis. Admittedly although
female literacy is often used as a surrogate for social
development, it need not be an adequate surrogate for
sanitation in an area. However poor sanitation by itself
cannot explain why the incidence of non-polio AFP
should increase year to year in the same area, in
proportion to doses of polio vaccine administered here,
unless sanitation in the area is deteriorating each year,
coinciding with increased vaccine doses administered.
Another possible explanation for the apparent
association could be increased surveillance of AFP in
areas where the polio related AFP is high, and this
may be detecting more cases of NPAFP. Though the
surveillance has improved over time, there is no
evidence to suggest that there are differences in the
quality of surveillance between states in the same year.
The difference in non-polio AFP rate between states in
any particular year cannot therefore be explained on
the basis of improved surveillance alone. In fact it is
the states with the best health indicators and therefore
presumably the best surveillance, (for example Goa
and Kerala) that have some of the lowest non-polio
AFP rates. The case definition of AFP has also
changed over the years but the definition at any point
of time has been uniform all over the country and so
this cannot explain the differences in the rates of non
polio AFP seen in different states in the same year.
Our findings point to the need for a critical appraisal to
find the factors contributing to the increase in
non-polio AFP with increase in OPV doses – perhaps
looking at the influence of strain shifts of
enteropathogens induced by the vaccine given
repatedly. The clear dose response relationship
indicates that this relationship in not a spurious one. In
1994 the Institute of Medicine of the National Academy
of Sciences, Washington had noted that the evidence
available to them favors acceptance of a causal
relation between Guillain-Barre syndrome (a major
component of the non polio AFP rate) and OPV. (15)
All these factors need to be examined.
Further studies perhaps including a rapid
epidemiological appraisal exploring the hypothesis of
association between number of doses of OPV and
NPAFP by case control studies, individual children
with NPAFP being the cases and matched healthy
children as the controls are called for.
Conclusion
Our observation showed positive association between
the non-polio AFP rate and the number of OPV doses.
Though there is a possibility that the apparent
association between the increasing trend of non-polio
AFP and OPV doses could be a statistical artifact due
to confounding factors, the magnitude of non-polio
AFP incidence and its increasing trend are public
health problems in themselves and need to be looked
into. We hope our findings will stimulate further work to
bring down the non-polio AFP incidence and if needed,
may also to rationalize and optimize the dose
schedule of the OPV.
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a Transforming World Economy, 2nd Edition
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National Polio Surveillance India updated data 2000 - 2012
NPSP Polio surveillance data on Acute Flaccid Paralysis (AFP) and non-polio AFP and Demographic data
State state year
poli
o afp
afp
rate
npaf
p
npafp
rate GDP
Percap gdp
(Rs 10,000)
Populatio
n
Densit
y Literacy
Female
literacy
Number
of dose
Andaman & Nicobar 1 1999 1567 0.00439981 356152 43 81 75 4
Andaman & Nicobar 1 2000 0 2 1.44 2 1.44 1567 0.00439981 356152 43 81 75 2
Andaman & Nicobar 1 2001 0 1 0.73 0 0 1567 0.00439981 356152 43 81 75 2
Andaman & Nicobar 1 2002 0 0 0 0 0 1567 0.00439981 356152 43 81 75 2
Andaman & Nicobar 1 2003 0 2 1.46 2 1.46 1567 0.00439981 356152 43 81 75
Andaman & Nicobar 1 2004 0 0 0 0 0 1567 0.00439981 356152 43 81 75 5
Andaman & Nicobar 1 2005 0 0 0 0 0 1567 0.00439981 356152 43 81 75 2
Andaman & Nicobar 1 2006 0 3 2.52 2 1.68 1567 0.00439981 356152 43 81 75 2
Andaman & Nicobar 1 2007 0 5 4.1 5 4.1 1567 0.00439981 356152 43 81 75 2
Andaman & Nicobar 1 2008 0 3 2.42 3 2.42 1567 0.00439981 356152 43 81 75 3.5
Andaman & Nicobar 1 2009 0 0 0 0 0 1567 0.00439981 356152 43 81 75 1.5
Andaman & Nicobar 1 2010 0 3 2.29 3 2.29 1567 0.00439981 356152 43 81 75 2
Andaman & Nicobar 1 2011 0 0 0 0 0 1567 0.00439981 356152 43 81 75 2
Andaman & Nicobar 1 2012 0 1 2.7 1 2.7 1567 0.00439981 356152 43 81 75 2
Andhra Pradesh 2 1999 236094 0.00309715 76210007 277 61 51 4.5
Andhra Pradesh 2 2000 0 373 1.38 365 1.35 236094 0.00309715 76210007 277 61 51 2
Andhra Pradesh 2 2001 0 342 1.17 332 1.14 236094 0.00309715 76210007 277 61 51 2
Andhra Pradesh 2 2002 0 371 1.27 369 1.27 236094 0.00309715 76210007 277 61 51 2
Andhra Pradesh 2 2003 19 474 1.58 401 1.34 236094 0.00309715 76210007 277 61 51 2.33
Andhra Pradesh 2 2004 1 468 1.55 462 1.53 236094 0.00309715 76210007 277 61 51 6
Illustrations
Illustration 1
Supplementary Data
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Andhra Pradesh 2 2005 0 740 2.74 738 2.73 236094 0.00309715 76210007 277 61 51 2
Andhra Pradesh 2 2006 0 566 2.09 507 1.87 236094 0.00309715 76210007 277 61 51 2
Andhra Pradesh 2 2007 5 777 2.84 767 2.8 236094 0.00309715 76210007 277 61 51 5.5
Andhra Pradesh 2 2008 1 756 2.62 753 2.61 236094 0.00309715 76210007 277 61 51 4
Andhra Pradesh 2 2009 0 855 3.08 851 3.07 236094 0.00309715 76210007 277 61 51 1.5
Andhra Pradesh 2 2010 0 857 3.04 794 2.82 236094 0.003097 76210007 277 61 51 2
Andhra Pradesh 2 2011 0 1110 3.88 1048 3.66 236094 0.003097 76210007 277 61 51 2
Andhra Pradesh 2 2012 0 1309 5.22 1270 5.06 236094 0.003097 76210007 277 61 51 2
Arunachal Pradesh 3 1999 2987 0.00272048 1097968 13 55 44 4
Arunachal Pradesh 3 2000 0 8 1.86 6 1.39 2987 0.00272048 1097968 13 55 44 2
Arunachal Pradesh 3 2001 0 6 1.34 6 1.34 2987 0.00272048 1097968 13 55 44 2
Arunachal Pradesh 3 2002 0 3 0.68 2 0.46 2987 0.00272048 1097968 13 55 44 2
Arunachal Pradesh 3 2004 0 6 1.23 6 1.23 2987 0.00272048 1097968 13 55 44 5
Arunachal Pradesh 3 2005 0 7 1.41 7 1.41 2987 0.00272048 1097968 13 55 44 2
Arunachal Pradesh 3 2006 0 12 2.42 7 1.41 2987 0.00272048 1097968 13 55 44 2
Arunachal Pradesh 3 2007 0 39 7.85 39 7.85 2987 0.00272048 1097968 13 55 44 2
Arunachal Pradesh 3 2008 0 48 9.38 48 9.38 2987 0.00272048 1097968 13 55 44 3.5
Arunachal Pradesh 3 2009 0 24 4.55 24 4.55 2987 0.00272048 1097968 13 55 44 1.5
Arunachal Pradesh 3 2010 0 15 2.75 12 2.2 2987 0.00272 1097968 13 55 44 2
Arunachal Pradesh 3 2011 0 37 6.57 34 6.04 2987 0.00272 1097968 13 55 44 2
Arunachal Pradesh 3 2012 0 36 6.47 35 6.29 2987 0.00272 1097968 13 55 44 2
Assam 4 1999 57543 0.00215876 26655528 340 64 56 6
Assam 4 2000 0 156 1.46 151 1.42 57543 0.00215876 26655528 340 64 56 2
Assam 4 2001 1 149 1.43 144 1.39 57543 0.00215876 26655528 340 64 56 2
Assam 4 2002 0 145 1.29 144 1.28 57543 0.00215876 26655528 340 64 56 2
Assam 4 2003 1 145 1.36 125 1.17 57543 0.00215876 26655528 340 64 56 2
Assam 4 2004 0 190 1.8 196 1.8 57543 0.00215876 26655528 340 64 56 6
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Assam 4 2005 0 285 2.57 283 2.55 57543 0.00215876 26655528 340 64 56 2
Assam 4 2006 2 360 3.1 315 2.71 57543 0.00215876 26655528 340 64 56 4
Assam 4 2007 0 536 4.5 535 4.49 57543 0.00215876 26655528 340 64 56 3.5
Assam 4 2008 1 475 3.9 470 3.87 57543 0.00215876 26655528 340 64 56 5.5
Assam 4 2009 0 542 4.41 539 4.39 57543 0.00215876 26655528 340 64 56 2.5
Assam 4 2010 0 429 3.45 404 3.25 57543 0.002159 26655528 340 64 56 2
Assam 4 2011 0 470 3.72 462 3.65 57543 0.002159 26655528 340 64 56 2
Assam 4 2012 0 586 4.74 580 4.69 57543 0.002159 26655528 340 64 56 2
Bihar 5 1999 79682 0.00096004 82998509 881 48 34 6
Bihar 5 2000 50 1444 3.46 1279 3.07 79682 0.00096004 82998509 881 48 34 4
Bihar 5 2001 27 711 2.14 646 1.95 79682 0.00096004 82998509 881 48 34 3
Bihar 5 2002 121 874 2.57 659 1.94 79682 0.00096004 82998509 881 48 34 4
Bihar 5 2003 17 800 2.3 644 1.85 79682 0.00096004 82998509 881 48 34
Bihar 5 2004 39 2183 6.15 2059 5.78 79682 0.00096004 82998509 881 48 34 6
Bihar 5 2005 30 5246 14.39 5110 14.02 79682 0.00096004 82998509 881 48 34 8
Bihar 5 2006 57 7087 18.99 6075 16.28 79682 0.00096004 82998509 881 48 34 7.5
Bihar 5 2007 503
1038
7 27.18 9723 25.44 79682 0.00096004 82998509 881 48 34 10.5
Bihar 5 2008 233
1165
9 29.67 11201 28.51 79682 0.00096004 82998509 881 48 34 10.5
Bihar 5 2009 117
1351
0 33.45 13206 32.7 79682 0.00096004 82998509 881 48 34 9.3
Bihar 5 2010 9
1558
5 37.53 14548 35.27 79682 0.00096 82998509 881 48 34 8
Bihar 5 2011 0
1761
6 41.27 17175 40.23 79682 0.00096 82998509 881 48 34 8
Bihar 5 2012 0
1587
4 37.42 15559 36.68 79682 0.00096 82998509 881 48 34 7
Chandigarh 6 1999 9872 0.0109611 900635 7900 82 77 4
Chandigarh 6 2000 1 8 2.49 7 2.18 9872 0.0109611 900635 7900 82 77 3
Chandigarh 6 2001 0 12 3.36 12 3.36 9872 0.0109611 900635 7900 82 77 2
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Chandigarh 6 2002 1 14 3.77 12 3.23 9872 0.0109611 900635 7900 82 77 2
Chandigarh 6 2003 0 3 0.78 3 0.78 9872 0.0109611 900635 7900 82 77
Chandigarh 6 2004 0 12 3 12 3 9872 0.0109611 900635 7900 82 77 5
Chandigarh 6 2005 0 9 2.17 9 2.17 9872 0.0109611 900635 7900 82 77 3
Chandigarh 6 2006 1 19 4.43 16 3.73 9872 0.0109611 900635 7900 82 77 4
Chandigarh 6 2007 0 14 3.16 14 3.16 9872 0.0109611 900635 7900 82 77 3.5
Chandigarh 6 2008 0 15 3.28 15 3.28 9872 0.0109611 900635 7900 82 77 5.5
Chandigarh 6 2009 0 24 4.52 24 4.52 9872 0.0109611 900635 7900 82 77 5.5
Chandigarh 6 2010 0 21 3.19 20 3.03 9872 0.010961 900635 7900 82 2
Chandigarh 6 2011 0 38 6.48 37 6.31 9872 0.010961 900635 7900 82 2
Chandigarh 6 2012 0 58 13.65 58 13.65 9872 0.010961 900635 7900 82 77 2
Chhattisgarh 7 1999 51921 0.002492 20833803 154 65 52 6
Chhattisgarh 7 2000 0 0 0 0 0 51921 0.002492 20833803 154 65 52 3
Chhattisgarh 7 2001 0 127 1.43 124 1.4 51921 0.002492 20833803 154 65 52 2
Chhattisgarh 7 2002 1 165 1.95 161 1.9 51921 0.002492 20833803 154 65 52 2
Chhattisgarh 7 2003 0 213 2.47 176 2.04 51921 0.002492 20833803 154 65 52
Chhattisgarh 7 2004 0 234 2.67 228 2.6 51921 0.002492 20833803 154 65 52 5
Chhattisgarh 7 2005 0 507 5.67 497 5.56 51921 0.002492 20833803 154 65 52 2
Chhattisgarh 7 2006 0 331 3.64 294 3.23 51921 0.002492 20833803 154 65 52 2
Chhattisgarh 7 2007 0 482 5.2 480 5.18 51921 0.002492 20833803 154 65 52 3.5
Chhattisgarh 7 2008 0 497 5.27 493 5.2 51921 0.002492 20833803 154 65 52 4.5
Chhattisgarh 7 2009 0 519 5.41 518 5.4 51921 0.002492 20833803 154 65 52 1.5
Chhattisgarh 7 2010 0 374 3.08 302 3.08 51921 0.002492 20833803 154 65 52 2
Chhattisgarh 7 2011 0 319 3.38 279 2.95 51921 0.002492 20833803 154 65 52 3
Chhattisgarh 7 2012 0 618 6.22 557 5.61 51921 0.002492 20833803 154 65 52 2
Dadra & Nagar
Haveli 8 1999 220490 449 60 43 6
Dadra & Nagar
Haveli 8 2000 0 1 1.44 1 1.44 220490 449 60 43 3
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Dadra & Nagar
Haveli 8 2001 0 1 1.14 1 1.14 220490 449 60 43 2
Dadra & Nagar
Haveli 8 2002 0 1 1.11 1 1.11 220490 449 60 43 2
Dadra & Nagar
Haveli 8 2003 0 0 0 0 0 220490 449 60 43
Dadra & Nagar
Haveli 8 2004 0 1 0.95 1 0.95 220490 449 60 43 6
Dadra & Nagar
Haveli 8 2005 0 1 0.91 1 0.91 220490 449 60 43 4
Dadra & Nagar
Haveli 8 2006 0 3 2.61 3 2.61 220490 449 60 43 4
Dadra & Nagar
Haveli 8 2007 0 3 2.61 3 2.61 220490 449 60 43 3.5
Dadra & Nagar
Haveli 8 2008 0 1 0.87 1 0.87 220490 449 60 43 3.5
Dadra & Nagar
Haveli 8 2009 0 5 4.31 5 4.31 220490 449 60 43 1.5
Dadra & Nagar
Haveli 8 2010 0 7 5.88 7 5.88 220490 449 60 43 2
Dadra & Nagar
Haveli 8 2011 0 4 2.82 4 2.82 220490 449 60 43 2
Dadra & Nagar
Haveli 8 2012 0 9 13.04 9 13.04 220490 449 60 43 2
Daman & Diu 9 1999 158204 1413 81 70 6
Daman & Diu 9 2000 0 1 1.99 1 1.99 158204 1413 81 70 3
Daman & Diu 9 2001 0 2 3.13 2 3.13 158204 1413 81 70 2
Daman & Diu 9 2002 0 1 1.54 1 1.54 158204 1413 81 70 2
Daman & Diu 9 2003 0 3 4.41 3 4.41 158204 1413 81 70
Daman & Diu 9 2004 0 0 0 0 0 158204 1413 81 70 6
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Daman & Diu 9 2005 0 1 1.25 1 1.25 158204 1413 81 70 4
Daman & Diu 9 2006 0 2 2.33 1 1.16 158204 1413 81 70 4
Daman & Diu 9 2007 0 4 4.4 4 4.4 158204 1413 81 70 3.5
Daman & Diu 9 2008 0 1 1.03 1 1.03 158204 1413 81 70 3.5
Daman & Diu 9 2009 0 3 2.91 3 2.91 158204 1413 81 70 1.5
Daman & Diu 9 2010 0 5 4.59 5 4.59 158204 1413 81 70 2
Daman & Diu 9 2011 0 6 5.35 6 5.35 158204 1413 81 70 2
Daman & Diu 9 2012 0 2 5.88 2 5.88 158204 1413 81 70 2
Delhi 10 1999 105385 0.0076087 13850507 9340 82 75
Delhi 10 2000 3 110 2.17 98 1.93 105385 0.0076087 13850507 9340 82 75 3
Delhi 10 2001 3 104 1.89 94 1.71 105385 0.0076087 13850507 9340 82 75 3
Delhi 10 2002 24 121 2.1 88 1.53 105385 0.0076087 13850507 9340 82 75 2
Delhi 10 2003 3 97 1.61 84 1.39 105385 0.0076087 13850507 9340 82 75
Delhi 10 2004 2 114 1.81 112 1.77 105385 0.0076087 13850507 9340 82 75 6
Delhi 10 2005 1 167 2.53 165 2.5 105385 0.0076087 13850507 9340 82 75 8
Delhi 10 2006 6 219 3.17 177 2.56 105385 0.0076087 13850507 9340 82 75 6.5
Delhi 10 2007 2 265 3.66 261 3.61 105385 0.0076087 13850507 9340 82 75 9.5
Delhi 10 2008 5 264 3.49 257 3.4 105385 0.0076087 13850507 9340 82 75 9.5
Delhi 10 2009 4 311 4.42 305 4.33 105385 0.0076087 13850507 9340 82 75 9.5
Delhi 10 2010 0 430 5.99 359 5.14 105385 0.007609 13850507 9340 82 75 8
Delhi 10 2011 0 707 8.57 675 8.18 105385 0.007609 13850507 9340 82 75 10
Delhi 10 2012 0 771 11.28 771 10.65 105385 0.007609 13850507 9340 82 75 7
Goa 11 1999 12400 0.009201 1347668 364 82 76 4
Goa 11 2000 0 19 3.29 18 3.12 12400 0.009201 1347668 364 82 76 2
Goa 11 2001 0 7 1.58 7 1.58 12400 0.009201 1347668 364 82 76 2
Goa 11 2002 0 5 1.12 5 1.12 12400 0.009201 1347668 364 82 76 2
Goa 11 2003 0 7 1.55 7 1.55 12400 0.009201 1347668 364 82 76
Goa 11 2004 0 10 2.16 10 2.16 12400 0.009201 1347668 364 82 76 5
Goa 11 2005 0 15 3.21 15 3.21 12400 0.009201 1347668 364 82 76 2
Goa 11 2006 0 8 1.68 7 1.47 12400 0.009201 1347668 364 82 76 2
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Goa 11 2007 0 32 6.67 32 6.67 12400 0.009201 1347668 364 82 76 2
Goa 11 2008 0 23 4.74 23 4.74 12400 0.009201 1347668 364 82 76 3.5
Goa 11 2009 0 13 2.63 13 2.63 12400 0.009201 1347668 364 82 76 1.5
Goa 11 2010 0 25 5.01 23 4.51 12400 0.009201 1347668 364 82 76 2
Goa 11 2011 0 26 6.65 24 6.14 12400 0.009201 1347668 364 82 76 2
Goa 11 2012 0 18 4.58 17 4.33 12400 0.009201 1347668 364 82 76 2
Gujarat 12 1999 216651 0.0042756 50671017 258 70 59 6
Gujarat 12 2000 2 313 1.83 286 1.67 216651 0.0042756 50671017 258 70 59 3
Gujarat 12 2001 1 306 1.51 298 1.47 216651 0.0042756 50671017 258 70 59 2.5
Gujarat 12 2002 24 348 1.7 310 1.51 216651 0.0042756 50671017 258 70 59 2
Gujarat 12 2003 3 378 1.8 323 1.54 216651 0.0042756 50671017 258 70 59
Gujarat 12 2004 0 432 1.97 431 1.97 216651 0.0042756 50671017 258 70 59 6
Gujarat 12 2005 1 565 2.53 557 2.49 216651 0.0042756 50671017 258 70 59 3
Gujarat 12 2006 4 563 2.49 513 2.27 216651 0.0042756 50671017 258 70 59 4
Gujarat 12 2007 1 844 4.2 838 4.17 216651 0.0042756 50671017 258 70 59 4.5
Gujarat 12 2008 0 699 3.4 698 3.4 216651 0.0042756 50671017 258 70 59 3.5
Gujarat 12 2009 0 793 3.78 792 3.77 216651 0.0042756 50671017 258 70 59 1.5
Gujarat 12 2010 0 908 4.23 849 3.96 216651 0.004276 50671017 258 70 59 2
Gujarat 12 2011 0 1031 4.71 1013 4.63 216651 0.004276 50671017 258 70 59 2
Gujarat 12 2012 0 938 4.36 910 4.23 216651 0.004276 50671017 258 70 59
Haryana 13 1999 106385 0.005031 21144564 478 69 56 4
Haryana 13 2000 4 194 2.46 176 2.23 106385 0.005031 21144564 478 69 56 3
Haryana 13 2001 5 220 2.64 206 2.47 106385 0.005031 21144564 478 69 56 2
Haryana 13 2002 37 273 3.18 218 2.54 106385 0.005031 21144564 478 69 56 2
Haryana 13 2003 3 247 2.8 223 2.53 106385 0.005031 21144564 478 69 56
Haryana 13 2004 2 315 3.43 309 3.41 106385 0.005031 21144564 478 69 56 6
Haryana 13 2005 1 423 4.55 417 4.49 106385 0.005031 21144564 478 69 56 5
Haryana 13 2006 18 439 4.57 362 3.76 106385 0.005031 21144564 478 69 56 5.25
Haryana 13 2007 6 554 5.61 538 5.44 106385 0.005031 21144564 478 69 56 5.5
Haryana 13 2008 2 568 5.59 559 5.5 106385 0.005031 21144564 478 69 56 7.25
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Haryana 13 2009 4 680 6.91 669 6.8 106385 0.005031 21144564 478 69 56 5.5
Haryana 13 2010 1 661 6.61 591 5.91 106385 0.005031 21144564 478 69 56 4
Haryana 13 2011 0 996 9.79 929 9.14 106385 0.005031 21144564 478 69 56 4.6
Haryana 13 2012 0 1379 13.48 1335 13.05 106385 0.005031 21144564 478 69 56
Himachal Pradesh 14 1999 25435 0.004184 6077900 109 77 68 4
Himachal Pradesh 14 2000 0 59 2.44 58 2.4 25435 0.004184 6077900 109 77 68 2
Himachal Pradesh 14 2001 0 44 1.86 44 1.86 25435 0.004184 6077900 109 77 68 2
Himachal Pradesh 14 2002 0 37 1.52 37 1.52 25435 0.004184 6077900 109 77 68 2
Himachal Pradesh 14 2003 0 30 1.22 27 1.1 25435 0.004184 6077900 109 77 68
Himachal Pradesh 14 2004 0 48 1.92 48 1.92 25435 0.004184 6077900 109 77 68 5
Himachal Pradesh 14 2005 0 48 1.89 46 1.8 25435 0.004184 6077900 109 77 68 2
Himachal Pradesh 14 2006 1 61 2.36 51 1.97 25435 0.004184 6077900 109 77 68 3
Himachal Pradesh 14 2007 0 95 3.6 95 3.61 25435 0.004184 6077900 109 77 68 2
Himachal Pradesh 14 2008 0 91 3.4 90 3.36 25435 0.004184 6077900 109 77 68 3.5
Himachal Pradesh 14 2009 1 103 4.77 102 4.72 25435 0.004184 6077900 109 77 68 1.5
Himachal Pradesh 14 2010 0 142 6.47 135 6.15 25435 0.004184 6077900 109 77 68 3
Himachal Pradesh 14 2011 0 141 6.32 134 6 25435 0.004184 6077900 109 77 68 2
Himachal Pradesh 14 2012 0 178 8.37 175 8.23 25435 0.004184 6077900 109 77 68 2
Jammu & Kashmir 15 1999 24265 0.00239212 10143700 46 54 41 4
Jammu & Kashmir 15 2000 0 80 2.21 79 2.18 24265 0.00239212 10143700 46 54 41 2
Jammu & Kashmir 15 2001 0 109 2.88 107 2.82 24265 0.00239212 10143700 46 54 41 2
Jammu & Kashmir 15 2002 1 77 1.85 76 1.82 24265 0.00239212 10143700 46 54 41 2
Jammu & Kashmir 15 2003 0 84 1.99 82 1.95 24265 0.00239212 10143700 46 54 41
Jammu & Kashmir 15 2004 0 90 2.09 90 2.09 24265 0.00239212 10143700 46 54 41 5
Jammu & Kashmir 15 2005 0 107 2.39 107 2.39 24265 0.00239212 10143700 46 54 41 2
Jammu & Kashmir 15 2006 1 146 3.2 140 3.07 24265 0.00239212 10143700 46 54 41 2
Jammu & Kashmir 15 2007 0 174 3.73 174 3.73 24265 0.00239212 10143700 46 54 41 2
Jammu & Kashmir 15 2008 0 140 2.93 140 2.93 24265 0.00239212 10143700 46 54 41 3.5
Jammu & Kashmir 15 2009 0 178 3.59 178 3.59 24265 0.00239212 10143700 46 54 41 1.5
Jammu & Kashmir 15 2010 1 191 3.72 189 3.68 24265 0.002392 10143700 46 54 41 4
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Jammu & Kashmir 15 2011 0 239 4.53 237 4.49 24265 0.002392 10143700 46 54 41 2
Jammu & Kashmir 15 2012 0 268 5.34 267 5.32 24265 0.002392 10143700 46 54 41 2
Jharkhand 16 1999 62950 0.0023361 26945829 338 54 39
Jharkhand 16 2000 0 0 0 0 0 62950 0.0023361 26945829 338 54 39 4
Jharkhand 16 2001 2 241 1.99 221 1.82 62950 0.0023361 26945829 338 54 39 2.5
Jharkhand 16 2002 12 281 2.62 252 2.35 62950 0.0023361 26945829 338 54 39 2
Jharkhand 16 2003 0 214 1.86 189 1.64 62950 0.0023361 26945829 338 54 39
Jharkhand 16 2004 0 395 2.48 386 3.4 62950 0.0023361 26945829 338 54 39 6
Jharkhand 16 2005 2 917 7.77 893 7.56 62950 0.0023361 26945829 338 54 39 4
Jharkhand 16 2006 1 912 7.55 835 6.92 62950 0.0023361 26945829 338 54 39 4
Jharkhand 16 2007 0 1368 11.1 1357 11.1 62950 0.0023361 26945829 338 54 39 4.5
Jharkhand 16 2008 0 1532 12.07 1522 12 62950 0.0023361 26945829 338 54 39 3.5
Jharkhand 16 2009 2 1493 11.38 1485 11.32 62950 0.0023361 26945829 338 54 39 1.5
Jharkhand 16 2010 8 1324 10.36 1170 9.15 62950 0.002336 26945829 338 54 39 5.33
Jharkhand 16 2011 0 1529 11.37 1465 10.9 62950 0.002336 26945829 338 54 39 6
Jharkhand 16 2012 0 1497 10.96 1418 10.4 62950 0.002336 26945829 338 54 39
Karnataka 17 1999 170741 0.00323 52850562 276 67 57 4
Karnataka 17 2000 8 317 1.7 283 1.52 170741 0.00323 52850562 276 67 57 2
Karnataka 17 2001 0 339 1.65 331 1.61 170741 0.00323 52850562 276 67 57 2.5
Karnataka 17 2002 0 318 1.52 315 1.5 170741 0.00323 52850562 276 67 57 2
Karnataka 17 2003 34 426 2.03 343 1.63 170741 0.00323 52850562 276 67 57 3
Karnataka 17 2004 1 503 2.32 497 2.29 170741 0.00323 52850562 276 67 57 6
Karnataka 17 2005 0 742 3.36 736 3.33 170741 0.00323 52850562 276 67 57 2
Karnataka 17 2006 0 595 2.62 536 2.36 170741 0.00323 52850562 276 67 57 3
Karnataka 17 2007 1 811 3.56 810 3.55 170741 0.00323 52850562 276 67 57 2.75
Karnataka 17 2008 0 751 4.01 750 4.01 170741 0.00323 52850562 276 67 57 3.5
Karnataka 17 2009 0 773 4.27 773 4.27 170741 0.00323 52850562 276 67 57 1.5
Karnataka 2010 0 841 4.41 749 3.93 170741 0.00323 52850562 276 67 57 2
Karnataka 17 2011 0 912 4.7 872 4.49 170741 0.00323 52850562 276 67 57 2
Karnataka 17 2012 0 995 5.27 954 5.05 170741 0.00323 52850562 276 67 57 2
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Kerala 18 1999 118998 0.003737 31841374 819 91 88 4
Kerala 18 2000 1 96 1.02 93 0.99 118998 0.003737 31841374 819 91 88 2
Kerala 18 2001 0 123 1.29 118 1.24 118998 0.003737 31841374 819 91 88 2
Kerala 18 2002 0 142 1.55 142 1.55 118998 0.003737 31841374 819 91 88 2
Kerala 18 2003 0 117 1.28 111 1.22 118998 0.003737 31841374 819 91 88
Kerala 18 2004 0 206 2.26 206 2.26 118998 0.003737 31841374 819 91 88 5
Kerala 18 2005 0 218 2.3 217 2.29 118998 0.003737 31841374 819 91 88 2
Kerala 18 2006 0 226 2.36 206 2.15 118998 0.003737 31841374 819 91 88 2
Kerala 18 2007 0 229 2.28 229 2.28 118998 0.003737 31841374 819 91 88 2
Kerala 18 2008 0 292 2.88 292 2.88 118998 0.003737 31841374 819 91 88 3.5
Kerala 18 2009 0 326 3.83 326 3.83 118998 0.003737 31841374 819 91 88 1.5
Kerala 18 2010 0 350 3.87 320 3.54 118998 0.003737 31841374 819 91 88 2
Kerala 18 2011 0 395 4.25 377 4.01 118998 0.003737 31841374 819 91 88 2
Kerala 18 2012 0 328 3.93 323 3.87 118998 0.003737 31841374 819 91 88 2
Lakshadweep 19 1999 60650 1895 88 82 4
Lakshadweep 19 2000 0 0 0 0 0 60650 1895 88 82 2
Lakshadweep 19 2001 0 0 0 0 0 60650 1895 88 82 2
Lakshadweep 19 2002 0 1 4.55 1 4.55 60650 1895 88 82 2
Lakshadweep 19 2003 0 0 0 0 0 60650 1895 88 82
Lakshadweep 19 2004 0 1 4.55 1 4.55 60650 1895 88 82 5
Lakshadweep 19 2005 0 1 4.17 1 4.17 60650 1895 88 82 2
Lakshadweep 19 2006 0 0 0 0 0 60650 1895 88 82 2
Lakshadweep 19 2007 0 1 4.17 1 4.17 60650 1895 88 82 2
Lakshadweep 19 2008 0 0 0 0 0 60650 1895 88 82 3.5
Lakshadweep 19 2009 0 0 0 0 0 60650 1895 88 82 1.5
Lakshadweep 19 2010 0 0 0 0 0 60650 1895 88 82 2
Lakshadweep 19 2011 0 0 0 0 0 60650 1895 88 82 2
Lakshadweep 19 2012 0 1 5.56 1 5.56 60650 1895 88 82 2
Madhya Pradesh 20 1999 116322 0.001927 60348023 196 64 50 6
Madhya Pradesh 20 2000 2 634 2.01 608 1.93 116322 0.001927 60348023 196 64 50 3
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Madhya Pradesh 20 2001 0 383 1.59 365 1.51 116322 0.001927 60348023 196 64 50 2.5
Madhya Pradesh 20 2002 21 497 2.02 452 1.84 116322 0.001927 60348023 196 64 50 2
Madhya Pradesh 20 2003 11 532 2.1 436 1.72 116322 0.001927 60348023 196 64 50 2
Madhya Pradesh 20 2004 0 772 2.98 747 2.88 116322 0.001927 60348023 196 64 50 6
Madhya Pradesh 20 2005 0 1141 4.3 1127 4.25 116322 0.001927 60348023 196 64 50 4.66
Madhya Pradesh 20 2006 3 1273 4.69 1071 3.95 116322 0.001927 60348023 196 64 50 6.33
Madhya Pradesh 20 2007 0 2145 7.74 2135 7.7 116322 0.001927 60348023 196 64 50 5.125
Madhya Pradesh 20 2008 1 2284 7.9 2274 7.86 116322 0.001927 60348023 196 64 50 6.5
Madhya Pradesh 20 2009 0 2722 9.41 2719 9.4 116322 0.001927 60348023 196 64 50 3.5
Madhya Pradesh 20 2010 0 2737 9.27 2477 8.39 116322 0.001927 60348023 196 64 50 4
Madhya Pradesh 20 2011 0 2814 9.33 2741 9.09 116322 0.001927 60348023 196 64 50 4
Madhya Pradesh 20 2012 0 2933 9.9 2835 9.57 116322 0.001927 60348023 196 64 50
Maharashtra 21 1999 432413 0.004463 96878627 315 77 68 4
Maharashtra 21 2000 7 598 1.84 562 1.73 432413 0.004463 96878627 315 77 68 2
Maharashtra 21 2001 4 601 1.8 579 1.73 432413 0.004463 96878627 315 77 68 2.5
Maharashtra 21 2002 6 592 1.73 571 1.67 432413 0.004463 96878627 315 77 68 3
Maharashtra 21 2003 3 710 2.04 634 1.82 432413 0.004463 96878627 315 77 68 2.5
Maharashtra 21 2004 3 818 2.3 808 2.28 432413 0.004463 96878627 315 77 68 5
Maharashtra 21 2005 0 1205 3.34 1200 3.33 432413 0.004463 96878627 315 77 68 4.66
Maharashtra 21 2006 5 1294 3.53 1119 3.05 432413 0.004463 96878627 315 77 68 5.25
Maharashtra 21 2007 2 1881 5.05 1873 5.03 432413 0.004463 96878627 315 77 68 5
Maharashtra 21 2008 2 1915 5.05 1908 5.05 432413 0.004463 96878627 315 77 68 5.5
Maharashtra 21 2009 0 2255 5.86 2255 5.86 432413 0.004463 96878627 315 77 68 5.5
Maharashtra 21 2010 5 2499 6.52 2318 6.05 432413 0.004463 96878627 315 77 68 6
Maharashtra 21 2011 0 2791 7.18 2711 6.97 432413 0.004463 96878627 315 77 68 5
Maharashtra 21 2012 0 3065 7.78 2980 7.56 432413 0.004463 96878627 315 77 68
Manipur 22 1999 5714 0.002637 2166788 97 69 60 4
Manipur 22 2000 0 16 1.76 14 1.54 5714 0.002637 2166788 97 69 60 2
Manipur 22 2001 0 14 1.37 14 1.37 5714 0.002637 2166788 97 69 60 2
Manipur 22 2002 0 9 0.95 9 0.95 5714 0.002637 2166788 97 69 60 2
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Manipur 22 2003 0 8 0.84 7 0.74 5714 0.002637 2166788 97 69 60
Manipur 22 2004 0 12 1.22 12 1.22 5714 0.002637 2166788 97 69 60 5
Manipur 22 2005 0 19 1.97 19 1.97 5714 0.002637 2166788 97 69 60 2
Manipur 22 2006 0 14 1.42 12 1.22 5714 0.002637 2166788 97 69 60 2
Manipur 22 2007 0 22 2.21 22 2.21 5714 0.002637 2166788 97 69 60 2
Manipur 22 2008 0 24 2.39 24 2.39 5714 0.002637 2166788 97 69 60 3.5
Manipur 22 2009 0 21 2.05 21 2.05 5714 0.002637 2166788 97 69 60 1.5
Manipur 22 2010 0 18 1.73 17 1.63 5714 0.002637 2166788 97 69 60 2
Manipur 22 2011 0 19 1.79 19 1.79 5714 0.002637 2166788 97 69 60 2
Manipur 22 2012 0 33 3.06 33 3.06 5714 0.002637 2166788 97 69 60 2
Meghalaya 23 1999 6470 0.00279 2318822 103 63 60 4
Meghalaya 23 2000 0 9 1.02 7 0.79 6470 0.00279 2318822 103 63 60 2
Meghalaya 23 2001 0 18 1.97 18 1.97 6470 0.00279 2318822 103 63 60 2
Meghalaya 23 2002 0 14 1.48 14 1.48 6470 0.00279 2318822 103 63 60 2
Meghalaya 23 2003 0 11 1.07 10 0.97 6470 0.00279 2318822 103 63 60 2
Meghalaya 23 2004 0 17 1.69 17 1.69 6470 0.00279 2318822 103 63 60 5
Meghalaya 23 2005 0 24 2.09 24 2.09 6470 0.00279 2318822 103 63 60 2
Meghalaya 23 2006 0 21 2.03 20 1.93 6470 0.00279 2318822 103 63 60 2
Meghalaya 23 2007 0 42 3.94 42 3.94 6470 0.00279 2318822 103 63 60 2
Meghalaya 23 2008 0 38 3.51 38 3.51 6470 0.00279 2318822 103 63 60 3.5
Meghalaya 23 2009 0 33 2.96 33 2.96 6470 0.00279 2318822 103 63 60 1.5
Meghalaya 23 2010 0 28 2.39 27 2.3 6470 0.00279 2318822 103 63 60 2
Meghalaya 23 2011 0 29 2.41 29 2.41 6470 0.00279 2318822 103 63 60 2
Meghalaya 23 2012 0 42 3.47 41 3.39 6470 0.00279 2318822 103 63 60 2
Mizoram 24 1999 2697 0.003035 888573 42 88 86
Mizoram 24 2000 0 11 3.19 11 3.19 2697 0.003035 888573 42 88 86 2
Mizoram 24 2001 0 4 1.14 4 1.14 2697 0.003035 888573 42 88 86 2
Mizoram 24 2002 0 4 1.2 4 1.2 2697 0.003035 888573 42 88 86 2
Mizoram 24 2003 0 2 0.59 2 0.59 2697 0.003035 888573 42 88 86
Mizoram 24 2004 0 0 0 0 0 2697 0.003035 888573 42 88 86 5
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Mizoram 24 2005 0 6 1.74 6 1.74 2697 0.003035 888573 42 88 86 2
Mizoram 24 2006 0 8 2.28 6 1.71 2697 0.003035 888573 42 88 86 2
Mizoram 24 2007 0 14 3.8 14 3.8 2697 0.003035 888573 42 88 86 2
Mizoram 24 2008 0 7 1.74 7 1.74 2697 0.003035 888573 42 88 86 3.5
Mizoram 24 2009 0 8 1.94 8 1.94 2697 0.003035 888573 42 88 86 1.5
Mizoram 24 2010 0 4 0.95 4 0.95 2697 0.003035 888573 42 88 86 2
Mizoram 24 2011 0 5 1.17 5 1.17 2697 0.003035 888573 42 88 86 2
Mizoram 24 2012 0 16 3.69 15 3.46 2697 0.003035 888573 42 88 86 2
Nagaland 25 1999 5346 0.00268638 1990036 120 67 62
Nagaland 25 2000 0 8 1.31 8 1.31 5346 0.00268638 1990036 120 67 62 2
Nagaland 25 2001 0 6 0.75 6 0.75 5346 0.00268638 1990036 120 67 62 2
Nagaland 25 2002 0 2 0.26 2 0.26 5346 0.00268638 1990036 120 67 62 2
Nagaland 25 2003 0 1 0.12 1 0.12 5346 0.00268638 1990036 120 67 62
Nagaland 25 2004 0 3 0.34 3 0.34 5346 0.00268638 1990036 120 67 62 5
Nagaland 25 2005 0 11 1.23 11 1.23 5346 0.00268638 1990036 120 67 62 2
Nagaland 25 2006 0 4 0.4 4 0.4 5346 0.00268638 1990036 120 67 62 2
Nagaland 25 2007 0 23 2.21 23 2.21 5346 0.00268638 1990036 120 67 62 2
Nagaland 25 2008 0 18 1.64 18 1.64 5346 0.00268638 1990036 120 67 62 3.5
Nagaland 25 2009 0 27 2.33 27 2.33 5346 0.00268638 1990036 120 67 62 1.5
Nagaland 25 2010 0 31 2.56 31 2.56 5346 0.002686 1990036 120 67 62 2
Nagaland 25 2011 0 34 4.18 33 4.05 5346 0.002686 1990036 120 67 62 2
Nagaland 25 2012 0 29 4.07 29 4.07 5346 0.002686 1990036 120 67 62 2
Orissa 26 1999 78536 0.00213386 36804660 236 64 51 3
Orissa 26 2000 0 273 2.1 259 1.99 78536 0.00213386 36804660 236 64 51 2
Orissa 26 2001 0 312 2.14 304 2.09 78536 0.00213386 36804660 236 64 51 2
Orissa 26 2002 4 267 1.83 262 1.8 78536 0.00213386 36804660 236 64 51 2
Orissa 26 2003 2 265 1.82 240 1.65 78536 0.00213386 36804660 236 64 51 2
Orissa 26 2004 0 284 1.9 278 1.85 78536 0.00213386 36804660 236 64 51 5
Orissa 26 2005 0 679 4.34 677 4.33 78536 0.00213386 36804660 236 64 51 2
Orissa 26 2006 0 850 5.35 730 4.59 78536 0.00213386 36804660 236 64 51 2
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Orissa 26 2007 1 1023 6.41 1017 6.37 78536 0.00213386 36804660 236 64 51 4.5
Orissa 26 2008 2 1227 7.59 1216 7.52 78536 0.00213386 36804660 236 64 51 4.5
Orissa 26 2009 0 1481 10.91 1473 10.85 78536 0.00213386 36804660 236 64 51 1.5
Orissa 26 2010 0 1506 10.96 1342 9.7 78536 0.002134 36804660 236 64 51 2
Orissa 26 2011 0 1157 8.32 1125 8.09 78536 0.002134 36804660 236 64 51 2
Orissa 26 2012 0 1996 14.18 1925 13.67 78536 0.002134 36804660 236 64 51 2
Pondicherry 27 1999 5700 0.00585 974345 2034 81 74 2
Pondicherry 27 2000 0 5 1.24 5 1.24 5700 0.00585 974345 2034 81 74 2
Pondicherry 27 2001 0 6 1.58 6 1.58 5700 0.00585 974345 2034 81 74 2
Pondicherry 27 2002 0 7 2.37 7 2.37 5700 0.00585 974345 2034 81 74 2
Pondicherry 27 2003 0 5 1.68 4 1.35 5700 0.00585 974345 2034 81 74
Pondicherry 27 2004 0 6 1.98 6 1.98 5700 0.00585 974345 2034 81 74 5
Pondicherry 27 2005 0 18 5.84 18 5.84 5700 0.00585 974345 2034 81 74 2
Pondicherry 27 2006 0 6 1.92 6 1.92 5700 0.00585 974345 2034 81 74 2
Pondicherry 27 2007 0 11 3.44 10 3.13 5700 0.00585 974345 2034 81 74 2
Pondicherry 27 2008 0 19 5.81 19 5.81 5700 0.00585 974345 2034 81 74 3.5
Pondicherry 27 2009 0 16 4.8 16 4.8 5700 0.00585 974345 2034 81 74 1.5
Pondicherry 27 2010 0 14 4.13 14 4.13 5700 0.00585 974345 2034 81 74 2
Pondicherry 27 2011 0 13 3.77 13 3.77 5700 0.00585 974345 2034 81 74 2
Pondicherry 27 2012 0 15 4.26 15 4.26 5700 0.00585 974345 2034 81 74 2
Punjab 28 1999 109735 0.00450491 24358999 484 70 64
Punjab 28 2000 0 214 2.59 203 2.46 109735 0.00450491 24358999 484 70 64 2
Punjab 28 2001 5 197 2.33 185 2.19 109735 0.00450491 24358999 484 70 64 2
Punjab 28 2002 2 175 2.03 169 1.96 109735 0.00450491 24358999 484 70 64 2
Punjab 28 2003 1 154 1.75 141 1.6 109735 0.00450491 24358999 484 70 64
Punjab 28 2004 0 215 2.4 213 2.38 109735 0.00450491 24358999 484 70 64 5
Punjab 28 2005 1 263 2.88 260 2.84 109735 0.00450491 24358999 484 70 64 2.5
Punjab 28 2006 8 238 2.55 208 2.23 109735 0.00450491 24358999 484 70 64 5.25
Punjab 28 2007 1 371 3.89 368 3.86 109735 0.00450491 24358999 484 70 64 4.5
Punjab 28 2008 2 389 4 383 3.94 109735 0.00450491 24358999 484 70 64 4.5
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Punjab 28 2009 4 457 4.61 450 4.53 109735 0.00450491 24358999 484 70 64 3.5
Punjab 28 2010 0 357 4.32 329 3.98 109735 0.004505 24358999 484 70 64 3
Punjab 28 2011 0 576 6.74 547 6.4 109735 0.004505 24358999 484 70 64 2
Punjab 28 2012 0 730 9.45 703 9.1 109735 0.004505 24358999 484 70 64
Rajasthan 29 1999 124224 0.00219837 56507188 165 61 44 3
Rajasthan 29 2000 0 536 2.42 504 2.27 124224 0.00219837 56507188 165 61 44 2
Rajasthan 29 2001 0 451 1.9 435 1.83 124224 0.00219837 56507188 165 61 44 2
Rajasthan 29 2002 41 466 2.01 402 1.73 124224 0.00219837 56507188 165 61 44 2
Rajasthan 29 2003 4 440 1.85 383 1.61 124224 0.00219837 56507188 165 61 44
Rajasthan 29 2004 0 624 2.59 613 2.54 124224 0.00219837 56507188 165 61 44 6
Rajasthan 29 2005 0 931 3.76 919 3.71 124224 0.00219837 56507188 165 61 44 4
Rajasthan 29 2006 1 1003 3.95 834 3.29 124224 0.00219837 56507188 165 61 44 5.25
Rajasthan 29 2007 3 1336 5.19 1323 5.14 124224 0.00219837 56507188 165 61 44 4.6
Rajasthan 29 2008 2 1353 5.08 1342 5.04 124224 0.00219837 56507188 165 61 44 6.5
Rajasthan 29 2009 3 1439 5.34 1430 5.3 124224 0.00219837 56507188 165 61 44 5.5
Rajasthan 29 2010 124224 0.002198 56507188 165 61 44 4
Rajasthan 29 2011 0 1823 6.47 1753 6.22 124224 0.002198 56507188 165 61 44 4.6
Rajasthan 29 2012 0 2053 7.36 1949 6.99 124224 0.002198 56507188 165 61 44
Sikkim 30 1999 1803 0.00333363 540851 76 70 61 2
Sikkim 30 2000 0 12 5.95 12 5.95 1803 0.00333363 540851 76 70 61 2
Sikkim 30 2001 0 4 1.84 4 1.84 1803 0.00333363 540851 76 70 61 2
Sikkim 30 2002 0 1 0.45 1 0.45 1803 0.00333363 540851 76 70 61 2
Sikkim 30 2003 0 3 1.32 3 1.32 1803 0.00333363 540851 76 70 61
Sikkim 30 2004 0 2 0.85 2 0.85 1803 0.00333363 540851 76 70 61 5
Sikkim 30 2005 0 2 0.82 2 0.82 1803 0.00333363 540851 76 70 61 2
Sikkim 30 2006 0 2 0.79 1 0.4 1803 0.00333363 540851 76 70 61 2
Sikkim 30 2007 0 6 2.31 6 2.31 1803 0.00333363 540851 76 70 61 2
Sikkim 30 2008 0 5 2.08 5 2.08 1803 0.00333363 540851 76 70 61 3.5
Sikkim 30 2009 0 3 1.22 3 1.22 1803 0.00333363 540851 76 70 61 1.5
Sikkim 30 2010 0 7 2.76 6 2.36 1803 0.003334 540851 76 70 61 2
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Sikkim 30 2011 0 8 3.05 8 3.05 1803 0.003334 540851 76 70 61 2
Sikkim 30 2012 0 7 3.26 7 3.26 1803 0.003334 540851 76 70 61 2
Tamil Nadu 31 1999 223528 0.00358185 62405679 480 73 65 2
Tamil Nadu 31 2000 0 292 1.55 275 1.46 223528 0.00358185 62405679 480 73 65 2
Tamil Nadu 31 2001 0 302 1.57 294 1.53 223528 0.00358185 62405679 480 73 65 2
Tamil Nadu 31 2002 0 287 1.55 286 1.54 223528 0.00358185 62405679 480 73 65 2
Tamil Nadu 31 2003 2 310 1.66 267 1.43 223528 0.00358185 62405679 480 73 65
Tamil Nadu 31 2004 1 398 2.1 395 2.09 223528 0.00358185 62405679 480 73 65 5
Tamil Nadu 31 2005 0 539 3.05 537 3.04 223528 0.00358185 62405679 480 73 65 2
Tamil Nadu 31 2006 0 423 2.37 376 2.11 223528 0.00358185 62405679 480 73 65 2
Tamil Nadu 31 2007 0 545 3.02 544 3.02 223528 0.00358185 62405679 480 73 65 2
Tamil Nadu 31 2008 0 557 3.06 557 3.06 223528 0.00358185 62405679 480 73 65 3.5
Tamil Nadu 31 2009 0 604 3.28 604 3.28 223528 0.00358185 62405679 480 73 65 1.5
Tamil Nadu 31 2010 0 602 3.55 570 3.45 223528 0.003582 62405679 480 73 65 2
Tamil Nadu 31 2011 0 622 3.76 607 3.67 223528 0.003582 62405679 480 73 65 2
Tamil Nadu 31 2012 0 655 3.72 630 3.58 223528 0.003582 62405679 480 73 65 2
Tripura 32 1999 9124 0.00285196 3199203 305 74 65 2
Tripura 32 2000 0 19 1.39 18 1.31 9124 0.00285196 3199203 305 74 65 2
Tripura 32 2001 0 20 1.57 20 1.57 9124 0.00285196 3199203 305 74 65 2
Tripura 32 2002 0 15 1.16 15 1.16 9124 0.00285196 3199203 305 74 65 2
Tripura 32 2003 0 8 0.61 6 0.46 9124 0.00285196 3199203 305 74 65
Tripura 32 2004 0 21 1.58 52 4.83 9124 0.00285196 3199203 305 74 65 5
Tripura 32 2005 2 54 5.01 52 4.83 9124 0.00285196 3199203 305 74 65 2
Tripura 32 2006 0 53 4.85 41 3.75 9124 0.00285196 3199203 305 74 65 4
Tripura 32 2007 0 79 5.84 79 5.84 9124 0.00285196 3199203 305 74 65 2
Tripura 32 2008 0 60 4.37 60 4.37 9124 0.00285196 3199203 305 74 65 3.5
Tripura 32 2009 0 60 4.22 60 4.22 9124 0.00285196 3199203 305 74 65 1.5
Tripura 32 2010 0 87 5.95 82 5.61 9124 0.002852 3199203 305 74 65 2
Tripura 32 2011 0 58 3.91 58 3.91 9124 0.002852 3199203 305 74 65 2
Tripura 32 2012 0 91 6.28 90 6.21 9124 0.002852 3199203 305 74 65 2
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Uttar Pradesh 33 1999 279762 0.00168331 166197921 690 57 43 4
Uttar Pradesh 33 2000 178 1847 2.64 1461 2.09 279762 0.00168331 166197921 690 57 43 3
Uttar Pradesh 33 2001 216 1871 2.82 1478 2.23 279762 0.00168331 166197921 690 57 43 4
Uttar Pradesh 33 2002 1242 3515 5.18 1845 2.72 279762 0.00168331 166197921 690 57 43 4
Uttar Pradesh 33 2003 83 1971 2.84 1562 2.25 279762 0.00168331 166197921 690 57 43
Uttar Pradesh 33 2004 82 4058 5.72 3789 5.34 279762 0.00168331 166197921 690 57 43 6
Uttar Pradesh 33 2005 29
1026
4 14.14 10055 13.83 279762 0.00168331 166197921 690 57 43 9
Uttar Pradesh 33 2006 519
1219
2 16.42 10271 13.83 279762 0.00168331 166197921 690 57 43 7.5
Uttar Pradesh 33 2007 341
1488
5 19.59 14343 18.88 279762 0.00168331 166197921 690 57 43 10.5
Uttar Pradesh 33 2008 305
1764
9 22.71 17108 22.01 279762 0.00168331 166197921 690 57 43 10.5
Uttar Pradesh 33 2009 602
1878
5 23.63 17931 22.56 279762 0.00168331 166197921 690 57 43 8.4
Uttar Pradesh 33 2010 10
2142
3 26.26 19453 23.85 279762 0.001683 166197921 690 57 43 8
Uttar Pradesh 33 2011 0
2237
4 26.82 21635 25.93 279762 0.001683 166197921 690 57 43 8
Uttar Pradesh 33 2012 0
2096
8 25.79 20560 25.29 279762 0.001683 166197921 690 57 43 7
Uttarakhand 34 1999 25776 0.00303627 8489349 159 72 60 4
Uttarakhand 34 2000 0 0 0 0 0 25776 0.00303627 8489349 159 72 60 2
Uttarakhand 34 2001 3 68 2 60 1.77 25776 0.00303627 8489349 159 72 60 2
Uttarakhand 34 2002 14 98 2.84 81 2.34 25776 0.00303627 8489349 159 72 60 4
Uttarakhand 34 2003 0 87 2.59 67 1.99 25776 0.00303627 8489349 159 72 60
Uttarakhand 34 2004 1 114 3.21 110 3.1 25776 0.00303627 8489349 159 72 60 5.5
Uttarakhand 34 2005 1 266 7.42 260 7.25 25776 0.00303627 8489349 159 72 60 5
Uttarakhand 34 2006 13 246 6.75 203 5.576 25776 0.00303627 8489349 159 72 60 5.25
Uttarakhand 34 2007 6 268 7.18 260 6.97 25776 0.00303627 8489349 159 72 60 4.7
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Uttarakhand 34 2008 1 372 9.79 368 9.68 25776 0.00303627 8489349 159 72 60 6.5
Uttarakhand 34 2009 4 347 8.98 339 8.77 25776 0.00303627 8489349 159 72 60 5.5
Uttarakhand 34 2010 0 352 9.03 331 8.49 25776 0.003036 8489349 159 72 60 4
Uttarakhand 34 2011 0 365 9.19 361 9.09 25776 0.003036 8489349 159 72 60 4
Uttarakhand 34 2012 0 423 10.27 410 9.95 25776 0.003036 8489349 159 72 60
West Bengal 35 1999 236044 0.00294407 80176197 903 69 60 4
West Bengal 35 2000 8 451 1.55 410 1.41 236044 0.00294407 80176197 903 69 60 3
West Bengal 35 2001 1 409 1.41 393 1.35 236044 0.00294407 80176197 903 69 60 3
West Bengal 35 2002 49 579 1.94 506 1.7 236044 0.00294407 80176197 903 69 60 3
West Bengal 35 2003 28 511 1.83 423 1.51 236044 0.00294407 80176197 903 69 60
West Bengal 35 2004 2 711 2.5 697 2.45 236044 0.00294407 80176197 903 69 60 6
West Bengal 35 2005 0 1628 5.7 1619 5.66 236044 0.00294407 80176197 903 69 60 5.5
West Bengal 35 2006 1 1895 6.48 1756 6 236044 0.00294407 80176197 903 69 60 6.33
West Bengal 35 2007 2 2253 7.53 2239 7.47 236044 0.00294407 80176197 903 69 60 2.75
West Bengal 35 2008 2 1853 6.07 1844 6.04 236044 0.00294407 80176197 903 69 60 6.5
West Bengal 35 2009 0 1995 6.42 1988 6.4 236044 0.00294407 80176197 903 69 60 1.5
West Bengal 35 2010 8 2084 6.31 1942 5.88 236044 0.002944 80176197 903 69 60 6
West Bengal 35 2011 1 2515 7.47 2446 7.24 236044 0.002944 80176197 903 69 60 6
West Bengal 35 2012 0 3147 9.95 3095 9.79 236044 0.002944 80176197 903 69 60
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... The recent study by Puliyel et al. showed a positive association between the non-AFP rate and a number of oral polio vaccine (OPV) doses delivered to the area [8]. However, the present report did not study the non-AFP rate as well as the effect of number of OPV doses as it was a hospital based study and a large proportion of study population was migratory population. ...
... The recent study by Puliyel et al. showed a positive association between the non-AFP rate and a number of oral polio vaccine (OPV) doses delivered to the area [8]. However, the present report did not study the non-AFP rate as well as the effect of number of OPV doses as it was a hospital based study and a large proportion of study population was migratory population. ...
Article
Full-text available
The feasibility of global polio eradication is being questioned as a result of continued transmission in a few localities that act as sources for outbreaks elsewhere. Perhaps the greatest challenge is in India, where transmission has persisted in Uttar Pradesh and Bihar despite high coverage with multiple doses of vaccine. We estimate key parameters governing the seasonal epidemics in these areas and show that high population density and poor sanitation cause persistence by not only facilitating transmission of poliovirus but also severely compromising the efficacy of the trivalent vaccine. We analyze strategies to counteract this and show that switching to monovalent vaccine may finally interrupt virus transmission.
Article
Objective: To find out the demographic characteristics and analyze the stool culture results of the Acute Flaccid Paralysis (AFP) cases presenting at Bahawal Victoria Hospital Bahawalpur during the year 2005. Methodology: It is a simple observational study conducted at Department of Pediatrics and EPI centre in Pediatric outpatient Department Bahawal Victoria Hospital Bahawalpur. Study was conducted from January 2005 to December 2005. All the AFP cases presenting at Bahawal Victoria Hospital Bahawalpur during the year 2005 were included. The data of these cases was analyzed regarding the demographic characteristics and stool culture results. Results: In 73 cases of AFP presenting during the year 2005 male to female ratio was 1:1 while rural to urban ratio was 2.9:1. In 71(97%) of the cases stool samples were sent for poliovirus isolation. In 64(90%) stool samples no virus was isolated. Enterovirus was isolated in 6(8.5%) stool samples. In one stool sample, vaccine poliovirus was isolated. In two cases stools could not be sent; one out of these two expired while the other one was already notified from another district. Conclusion: Active surveillance of all AFP cases is mandatory to get the Polio eradicated. In this way all the cases of Poliomyelitis can be picked up and necessary measures can be taken.
Article
In September 1993, the Institute of Medicine released a report entitled Adverse Events Associated With Childhood Vaccines: Evidence Bearing on Causality. The report examined putative serious adverse consequences associated with administration of diphtheria and tetanus toxoids; measles, mumps, and measles-mumps-rubella vaccines; oral polio vaccine and inactivated polio vaccine; hepatitis B vaccines; and Haemophilus influenzae type b (Hib) vaccines. The committee spent 18 months reviewing all available scientific and medical data, from individual case reports (published and unpublished) to controlled clinical trials. The committee found that the evidence favored the rejection of a causal relation between diphtheria and tetanus toxoids and encephalopathy, infantile spasms, and sudden infant death syndrome, and between conjugate Hib vaccines and susceptibility to Hib disease. The committee found that the evidence favored acceptance of a causal relation between diphtheria and tetanus toxoids and Guillain-Barré syndrome and brachial neuritis, between measles vaccine and anaphylaxis, between oral polio vaccine and Guillain-Barré syndrome, and between unconjugated Hib vaccine and susceptibility to Hib disease. The committee found that the evidence established causality between diphtheria and tetanus toxoids and anaphylaxis, between measles vaccine and death from measles vaccine-strain viral infection, between measles-mumps-rubella vaccine and thrombocytopenia and anaphylaxis, between oral polio vaccine and poliomyelitis and death from polio vaccine-strain viral infection, and between hepatitis B vaccine and anaphylaxis. For five vaccine-related adverse events, there was no evidence identified. For the remaining 33 vaccine-related adverse events, the evidence was inadequate to accept or reject a causal relation.
Article
Between June 1988 to January 1991 a total of 246 children with acute flaccid paralysis (AFP) were seen at Hospital Infantil de México, Federico Gómez which was the center of study for AFP for the Poliomyelitis Eradication Program of Mexico. Of the 246 children, 42 has poliomyelitis (17%); 156 has Guillain-Barré syndrome (GBS) (63.4%); 16 had traumatic neuritis of the sciatic nerve secondary to IM injections (TNC) (6.5%); five had transverse myelitis (2%); the rest (27) had other diseases misdiagnosed as polio (10.9%). The basic clinical characteristics for the diagnosis of poliomyelitis are: myalgias and fever at the onset AFP, paralysis is asymmetrical, of distal predominance and causes severe muscular atrophy and skeletal deformities; the GBS presents as an ascending, symmetrical, areflexic paralysis of distal predominance. It does not causes atrophy or deformities. TNC presents several days after IM injections with pain and hypothermia in the affected limbs; TM is a flaccid, symmetrical paraparesis with neurogenic bladder and a sensory level. CSF and neurophysiological studies (EMG and NCV) are very useful for diagnosis. Other entities misdiagnosed as poliomyelitis were: osteoarticular trauma, myopathies and dystrophies, viral myositis, acute cerebellitis, retroperitoneal tumors and upper motor neuron syndromes. Viral studies in stool specimens are essential for the diagnosis of poliomyelitis.
  • Marx
Marx et al., Epidemiologic Reviews, 2000, Vol 22(2): 298-316.
Quoted in Wikipedia: List of states and union territories of India by population Comparative Economics in a Transforming World Economy
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  • Mv Rosser
http://www.censusindia.gov.in/Census_And_You/area _and_population.aspx. Quoted in Wikipedia: List of states and union territories of India by population. http://en.wikipedia.org/wiki/List_of_states_and_union_t erritories_of_India_by_population 12. Rosser JB, Rosser MV. Comparative Economics in a Transforming World Economy, 2nd Edition Massachusetts MIT Press ISBN 0-262-18234-3 (2004) Page 476
Surveillance Canadian Pediatric Surveillance Programme Acute Flaccid Paralysis
  • Canadian Pediatric
  • Society
Canadian Pediatric Society. Surveillance Canadian Pediatric Surveillance Programme Acute Flaccid Paralysis. http://www.cps.ca/english/Surveillance/CPSP/Studies/ acute.htm
WHO / UNICEF Joint Monitoring Programme (JMP) for Water Supply and Sanitation. http://www.wssinfo.org/data-estimates/introduction/ Accessed on 15 Adverse events associated with childhood vaccines other than pertussis and rubella
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  • Rb Johnston
Census of India 2001--State wise population totals file:///C:/Documents%20and%20Settings/Admin/Deskt op/AFP%20Polio/Literacy.htm 14. WHO / UNICEF Joint Monitoring Programme (JMP) for Water Supply and Sanitation. http://www.wssinfo.org/data-estimates/introduction/ Accessed on 15/5/12 15. Stratton KR, Howe CJ, Johnston RB. Adverse events associated with childhood vaccines other than pertussis and rubella. Summary of a report from the Institute of Medicine. JAMA. 1994;271:1602-5.