PowerPoint - CAP-TB

Report
Recent Epidemiologic Situations of TB in
Myanmar
-Preliminary Review of Data from routine
TB surveillance focusing on Case Finding9 May 2014, Nay Pyi Taw
Norio Yamada, RIT/JATA
JICA MIDCP
Today’s presentation
• All information from NTP
– Please don’t expect new things from the presentation
• Not formal presentation of confirmed results.
• Showing some way of looking at data
– The results are preliminary. I may be wrong.
• This can be a practice for Epi Review for NTP
review in December.
• Focusing on change in case finding because the
prevalence survey results indicate needs of
improving CF.
Limitation of Surveillance Data : The Onion Model
No access to health care
Access to health facilities,
but don't go
Presenting to health
facilities, but
undiagnosed
Diagnosed by public or
private providers, but not
notified
Diagnosed by NTP or
collaborating providers
Recorded in
notification data
Undiagnosed
cases
All TB cases
Diagnosed but
not notified
cases
Notified
cases
(WHO)
We may be able to see only some part of real TB problems from TB surveillance.
Interpretation should be carefully done:
-Either improvement of NTP or real increase in TB lead to increase in TB notifications.
-Either decrease in efforts or real decrease in TB lead to decrease in TB notifications.
Another limitation: Pop data
• Current population data may not be accurate.
• Pop movement from rural to urban.
– Urban population is likely to be underestimated.
– Rural population is likely to be underestimated
• Re-assessment of indicators by area and age
group based on pop census 2014 should be
made once census data become available.
Long Term Trend of Case Notification and
NTP development (NTP + Other Units)
350
305
294
300
CNR per 100000 population
279
240
250
228
195
Mainly reflecting
expansion of NTP
coverage by basic units
150
155
-Mainly reflecting strengthening
Case Finding and surveillance
-Influence of HIV?
126
100
0
240
210
200
50
263
101
65
45
144 TSP
84
74
58
52
63
231 TSP
324 TSP
CNR of All TB cases
297
Impact of HIV epidemic on TB trends
12%
10%
Trend of HIV prevalence among New TB patients HSS 20052013
10.4%
10.3%
10.8%
9.8%
11.1%
9.2%
9.9%
9.7%
9.2%
2012
2013
8%
6%
4%
2%
0%
2005
2006
2007
2008
2009
2010
2011
HIV is strong risk factor for TB. Therefore it is necessary to assess its impact.
According to HSS 2005-2013, about 10% of cases may be attributable directly to HIV
infection.
HIV prevalence by age and sex is helpful for assessing influence of HIV on TB trend.
Prediction in future requires trend of HIV prevalence in population.
Proportion of All forms of TB Patients contributed by NTP & Other reporting units
(2013)
PPM Hospitals
(3.3%)
MSF- H (2.8%)
PSI (15.3%)
MMA (2.1%)
MDM (0.1%)
AHRN (0.3%)
MSF-CH(0.3%)
NTP (75.8%)
PPM is considered as one of major contributors for increase in case notification through
case finding and reporting.
Recently intensified efforts of Case
Finding and TB surveillance
• PPM with partners: guidelines in 2005
• Childhood TB diagnosis
Case Finding has been intensified based on the findings from
the prevalence survey in 2009/2010
• Definitions of presumptive TB:
– 3week cough-> 2week
• Contact examination
• Access to diagnostic service
– Physical access: SCC, TB lab at SH, Mobile Team
– CBTBC, Drug sellers
“Is there any observation in TB surveillance suggesting impact of
efforts?”
Childhood and Adult Cases
• Usually source of infection is adult TB cases
• Early diagnosis of Adult TB cases
Reduction of TB transmission
Decrease in TB incidence
• Diagnosis of childhood TB cases is more
complicated.
• Better to see the trend of Childhood TB cases
and non-Childhood TB cases separately.
Recent Trend of TB cases of Childhood
and non-Childhood (NTP + Other Units)
• Childhood TB Cases increased.
• Adult cases are stable compared to childhood cases.
Trend of TB suspects and TB cases of
non-childhood (NTP + Partners)
Assuming childhood suspects has no smear-examination and no smear positive cases.
Trend of TB suspects and TB cases of
non-childhood
• Proportion of TB cases among suspects has
decreased since number of suspects sharply
increased.
• This may indicate coverage of Case Finding has
improved.
• The graph may suggest need of assessing
situations of smear-negative case diagnosis for
further strengthening Case Finding (early
detection).
Category of Regions & States According to Case Detection Rate of NSS(+)
(2001- 2013)
Still a wide Range of Notification Rate and CDR while overall increase.
Is it attributable mainly to performance or real difference of TB incidence?
Issues on assessment of Case Finding
achievements at Sub-country levels
• CDR is based on estimates of incidence rate and
population data
• It is difficult to obtain accurate estimates for
subnational levels (e.g. state/region, townships)
• It is necessary to assess not only achievement but
efforts of Case Finding.
• Additional tools might be required to assess
situation of Case Finding.
• There is no single tool of assessing situations of
Case Finding. We need to interpret several
indicators collectively.
Case Finding efforts and Results
Suspect Rate and Smear-Positivity Rate
Data from presentations
of laboratory evaluation
meeting 2014 is used.
In 2013, there are still variations in both suspect rates and positivity rates.
Reasons for variation in positivity rate for similar suspects rate need to be
investigated.
Areas with low suspect rate and high positivity rate might need to increase CF
efforts.
Gap between Notification and Prevalence
• Gap tended to be larger among elderly group
 Notified cases should once increase among elderly.
• Geographically States tended to have larger gap.
Trend of New+ by Age Group
(NTP + Other Units)
Change in Notified New+
By Age Group (NTP+ Other Units)
Larger increase is observed among elderly groups after 2010.
Average Age of New S+
15 -64 Years(NTP + Other Units)
When TB decrease, average age of TB cases is expected to increase because TB cases
from recent infection (young cases) decrease more rapidly than TB from remote
infection (elderly cases).
Increase in average age is observed. It might be attributable to improvement of CF
among elderly groups.
Hot Spot?
• Prevalence survey indicate high prevalence in
urban and remote areas
– Urban: probably due to higher incidence
– Remote: probably due to low case detection
Case Detection by Mobile Team in South
Dagon Township, Yangon (2012-2013)
Summary
• Some of observations from the routine data might indicate Case
Finding is going in right direction and TB is going down.
– The number and proportion of elderly cases increase: This might
suggest reduction of gap between prevalence and notification
– Average age has started increasing.
• However we need to investigate variations in case finding situations
and TB problems by subgroup of population, such as:
– Areas with low suspect rate with high smear positivity rate: unreached
area/population
– Areas with internal migrants.
– Age groups: Clear decline of New+ among young age group has not
been observed yet.
– HIV impact on some subgroup (age group, sex, areas)
• Information on situations of smear-negative case diagnosis is
limited.
Some of recommendations for further
assessment
•
•
•
•
•
•
•
Re-assessing indicators for recent years by using census population of 2014.
- For NTP review 2014 if census data become available in time.
Trends of Childhood and Adult TB cases should be separately assessed.
Analysis of age group distribution of presumptive TB and non-smear positive cases as well as
New S+ cases to understand trends of childhood and adult cases separately.
Assessment of suspect rates and smear-positivity rates separately for regular passive case
finding and active case finding.
Information on situations of smear-negative case diagnosis should be investigated for
accelerating early case detection appropriately.
Assessing the situations of CF in areas with very high and low smear-positivity rate and with
low suspect rates
– Assessment of health service delivery system (access to health service)
– Delay
– Way of identifying TB suspects
– Cases found by Mobile team
– Efforts should be strengthened until positivity rate goes down below 15%.
Analysis of HIV co-infection on TB trend: age group, sex and areas

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