Recent Epidemiologic Situations of TB in Myanmar

-Preliminary Review of Data from routine TB surveillance focusing on Case Finding-

9 May 2014, Nay Pyi Taw

Norio Yamada, RIT/JATAJICA 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

All TB cases

Undiagnosed cases

Diagnosed but not notified cases

Notified casesRecorded in

notification data

Diagnosed by NTP or collaborating providers

Diagnosed by public or private providers, but not

notified

Access to health facilities, but don't go

No access to health care

Presenting to health facilities, but undiagnosed

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.

(WHO)

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)

0

50

100

150

200

250

300

350

4565 74

58 5263

84101

126

155

195210

228

240240

263279

294305

297

CNR of All TB cases

CNR

per 1

0000

0 po

pula

tion

144 TSP

231 TSP 324 TSP

Mainly reflecting expan-sion of NTP coverage by basic units -Mainly reflecting strengthening

Case Finding and surveillance-Influence of HIV?

Impact of HIV epidemic on TB trends

2005 2006 2007 2008 2009 2010 2011 2012 20130%

2%

4%

6%

8%

10%

12%

10.3% 10.8% 9.8%11.1% 9.2%

10.4%9.9% 9.7% 9.2%

Trend of HIV prevalence among New TB patients HSS 2005-2013

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 diagnosisCase 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 casesÞReduction of TB transmission ÞDecrease 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 ResultsSuspect Rate and Smear-Positivity Rate

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.

Data from presentations of laboratory evaluation meeting 2014 is used.

Gap between Notification and Prevalence• Gap tended to be larger among elderly groupÞ 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