Valerie d acremont

Epidemiology and Public Health

Diagnostic parasitologique des accès

palustres: acquis et défis

Valérie D‘Acremont, MD, PhD

Atelier paludisme Madagascar, 22 Mars 2011

How to deal with malaria in patients?

Prompt treatment

Suspected malaria

Early and accurate diagnosis

What is ‘malaria’?

Different definitions depending on the purpose:

1) For epidemiological analysis (malaria infection)

� quantify burden of malaria, modelling...

2) For clinical management (malaria disease)

� to decide who should be treated for an

episode of malaria

Definitions of malaria

What is a true malaria episode (= illness) ?

CoughDiarrhea

ArthralgiaHeadache

General

population

Sick population

Febrile patients

‘Clinical malaria’

What is a true malaria episode (= illness) ?

General

population

Sick population

Febrile patients

Parasites in blood

‘Clinical malaria’

What is a true malaria episode (= illness) ?

‘Clinical malaria’

‘Malaria episode’

General

population

Febrile patients

Sick population

Parasites in blood

What is a true malaria episode (= illness) ?

CoughDiarrhea

ArthralgiaHeadache

Sick population

General

population

Parasites in blood

Sick people withincidental parasitemia

What is a true malaria episode (= illness) ?

‘Clinical malaria’

‘Malaria episode’

General

population

Febrile patients

Sick population

Sick people withincidental parasitemia

OVERDIAGNOSIS

What is a true malaria episode (= illness) ?

‘Malaria episode’

General

population

Febrile patients

Sick population

HEALTH FACILITIES:

Only patients that

should be treated !

Parasites in blood

In the context of elimination ?

General

population

Parasitemia in healthy people

Sick population

Febrile patients

Parasites in blood

POPULATION SURVEYS:

Treatment of the

hidden reservoir

Magnitude of overdiagnosis

Systematic review of 39 studies performed between 1986 and 2007

in 16 African countries including 42,979 patients

Proportion of feversassociated with Pf (%)

0

10

20

30

40

50

60

70

80

90

100

<2000 >2000

44%

22%

D’Acremont, CID 2010

Systematic review

Proportion of malaria among fevers in children < 5 years

81%1986Tanzania (rural)

5%2003Dar es Salaam

57%1995

38%1997

21%2005

4%2004Highlands

urbanruralYearCountry

Rooth, Font, Nsimba, Reyburn, Wang

Systematic review

Studies providing stratified values of PFPf

by age groups, including older children:

<5 years MEDIAN PR = 27% (IQR 20-50%)

5-14 years MEDIAN PR = 40% (IQR 22-48%)

>15 years MEDIAN PR = 24% (IQR 11-27%)

Consequences of over-treatment

Drugs wastage

Left untreatedfor real cause

Reattendances

Costs for patient

Parasite resistanceMistrust

in ACT

Predictors for malaria:

Clinical diagnosis: impossible to rely on it

0

Proportion of malaria

among fevers

Drug wastage (overdiagnosis)

20% 40% 60% 80% 100%

20%

40%

60%

80%

100%

Failure to treat (missed cases)

Reviewed by

Chandramohan et al

in 2002

high temperature of short duration

, absence of abdominal pain, absence of rash

, absence of cough

splenomegaly

How to deal with malaria in patients?

Prompt treatment

Suspected malaria

Early and accurate diagnosisLAB TEST

How to get universal access to

parasitological diagnosis?

Available malaria tests: microscopy

REGIONAL COURSE ON TRAINING OF TRAINERS ON USE OF

MALARIA RAPID DIAGNOSTIC TESTS (RDTS)

Components of good microscopy performance

Competency

Selection

Training

Assessment

Equipment/

reagents

Support networkSlide /results delivery

Work

environment

Performance

Supervisione.g. cross-checking??

Performance of Microscopy for malaria in DSM

Sensitivity = how sensitive is the test to detect the true positive cases

Specificity = how specific is the test to detect the true negative cases

Total

Total

Negative

Positive

Routine microscopy

NegativePositive

Expert microscopy

Sensitivity

= 70%

Specificity

= 45%

328322

148

173

2

5

7

178

150

0

20

40

60

80

100

120

140

0 -<

1010

-<10

010

0 -<

1000

1'00

0 -<

10'0

00

10'0

00 -<

100'

000

>100'

000

Reported parasitemia: routine versus expert

Real positives…

Routine microscopy

Expert microscopy

Parasitemia (parasites/µl)

Number of slides

hospitals 41%

health cent. 49%

dispensaries 65%

(range 13-90%)

Performance of Microscopy for malaria in

other places

In some places, problem of sensitivity

� cases missed:

71% in Moshi Reyburn et al, 2007

But more often, bad specificity

� overdiagnosis:

62% in Kenya Zurovac et al, 2006

Consequences of suboptimal

microscopy for malaria

1) Clinicians do not trust microscopy � overtreatment

Kenya, 2002:

- blood slide performed in 79% of febrile patients

and in 51% of afebrile patients

- 43% (routine) versus 13% (expert) positive slides

- 96% of positive and 79% of negative malaria patients

received treatmentZurovac et al, 2006

High mortality among patients admitted to hospital and incorrectly treated for

malaria, 10 hospitals, NE Tanzania

Admissions for malaria n=17,313Admissions for malaria n=17,313

Severe disease n=4670 (27%)Severe disease n=4670 (27%)

Readable slide results n=4474 (95%)Readable slide results n=4474 (95%)

No criteria forsevere disease n=12,643 (73%)120 deaths (1%)

No criteria forsevere disease n=12,643 (73%)120 deaths (1%)

Expert microscopy negativen=2412 (54%)

Expert microscopy negativen=2412 (54%)

Deadn=142 (7%)

Deadn=142 (7%)

Aliven=1920 (93%)

Aliven=1920 (93%)

Deadn=292 (12%)

Deadn=292 (12%)

Aliven=2120 (88%)

Aliven=2120 (88%)

Expert microscopy positiven=2062 (46%)

Expert microscopy positiven=2062 (46%)

Reyburn H et al. BMJ 2006

2) Clinicians tend to ignore non-malarial fevers

High mortality among patients admitted to hospital and incorrectly treated for

malaria, 10 hospitals, NE Tanzania

Admissions for malaria n=17,313Admissions for malaria n=17,313

Severe disease n=4670 (27%)Severe disease n=4670 (27%)

Readable slide results n=4474 (95%)Readable slide results n=4474 (95%)

No criteria forsevere disease n=12,643 (73%)120 deaths (1%)

No criteria forsevere disease n=12,643 (73%)120 deaths (1%)

Expert microscopy negativen=2412 (54%)

Expert microscopy negativen=2412 (54%)

Deadn=142 (7%)

Deadn=142 (7%)

Aliven=1920 (93%)

Aliven=1920 (93%)

Deadn=292 (12%)

Deadn=292 (12%)

Aliven=2120 (88%)

Aliven=2120 (88%)

Expert microscopy positiven=2062 (46%)

Expert microscopy positiven=2062 (46%)

Reyburn H et al. BMJ 2006

2) Clinicians tend to ignore non-malarial fevers

Dar es Salaam (Muhimbili hospital)

‘cerebral malaria’

22% in slide negative patients13% in slide positive patients

Makani et al 2003

A reliable test available at time and place of need,

used for more than 15 years in Europe

and 7 years in South Africa...

Add another malaria diagnostic test

Meta-analysis published in 2006:

HRP2 RDT at least as sensitiveas expert microscopy

REF: Ochola Lancet Infect Dis 2006

100%

90

80

70

60

50

40

30

20

10

0

Microscopy

HRP2 RDT

pLDH RDT

QBCAO

Sensitivity in the absence of a gold standard

Relative performance of each method

Technologies evolve quickly :

REF: Bell AJTMH 2005 Dal-Bianco AJTMH 2007 Stauffer CID 2009

Stauffer 2009

Dal-Bianco2007

Bell 2005

Author, year

SensitivityProportion

RDT(+) / BS(-)

positives by PCR

88%100%60%Travelers USA

22%46%80%Gabon

70%?91%92%Philippines

MicroscopyRDT

Origin of the samples

Conclusion: between 60 and 90% of so-called false-positive RDT

are real positives, reflecting the high sensitivity of HRP2 RDT

Relative performance of each method

Putative explanation for greater sensitivity of a RDT

relying on detection of a persistent antigen

REF: Bell AJTMH 2005

Relative performance of each method

Objective

To evaluate in an uncontrolled setting the

safety (clinical outcome) of withholding antimalarials

in febrile children with a negative RDT

in a moderately endemic area (urban setting)

in a highly endemic area (rural setting)

Safety study of RDT in Tanzania

1000

febrile children

603 (60%) RDTm -ve

396

followed up

591 followed up

387 (98%)

cured573 (97%)

cured

18 (3%)

still sick

15 RDTm -ve

2 RDTm still +ve

1 still no RDTm

1 LOF 12 LOF

2 LOF

2 RDT -ve

9 (2%)

still sick

BS negative

8 cured

1 LOF

1 admitted

2 deceased2 RDTm&BS -ve

14

cured

1 admitted1 RDTm&BS -ve

Day

0 D

ay

7 >

Da

y14

397 (40%) RDTm +ve

Translation of research findings into policy

Translation of research findings into policy

Improve laboratory diagnosis for malaria

in routine management of fever cases at

OPD

Implementation of RDT in Dar es Salaam

Intervention:

Pilot implementation

of RDT in Dar es Salaam

in the 3 district hospitals,

3 health centres

and 3 dispensaries

Methodology

Consultation process:

Baseline survey9 Intervention HF

Consultation process:

Post-intervention survey9 Intervention HF

INTERVENTIONTraining, RDTm implementation, quaterly supervision

3. Routine statistics of Health Facilities

Consultation process:3 Control HF

Consultation process:

3 Control HF

2. Cluster randomizedstudy

1. Before and afterstudy

2007 20082006

1. Before-after cluster randomized study

Patients with history of fever

Proportions of patients treated with antimalarials

9 intervention HF

BEFORE AFTER

3 control HF

81%

24%

65%

0%

20%

40%

60%

80%

100%

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n

Fe

b

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r

Ma

y

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n

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Au

g

Se

p

Oc

t

No

v

De

c

Ja

n

Fe

b

Ma

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r

Ma

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Ju

n

Ju

l

Au

g

Se

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Oc

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No

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ate

1) Performance of routine mRDT much better than

routine microscopy

� better specificity � less overdiagnosis

mRDT implementation

2006 2007 2008

Routine microscopy48%

Routine RDT8%

Results 1: why did it work?

2) Negative RDT patients are not treated for malaria

more trust in mRDT � better adherence to the guidelines

Negative patients treated

With microscopy With mRDT

53%

7%

Results 1: why did it work?

0

5000

10000

15000

20000

25000Jan

Feb

Mar

Apr

May

Jun

Jul

Aug

Sep

Oct

Nov

Dec

Jan

Feb

Mar

Apr

May

Jun

Jul

Aug

Sep

dispensary 3

dispensary 2

dispensary 1

health centre 3

health centre 2

health centre 1

hospital 3

hospital 2

hospital 1

mRDT

2007 2008

Results 2: longitudinal study

Artemether/lumefantrine (ALu)

0

2000

4000

6000

8000

10000

12000

14000

16000

18000

Jan

Mar

May

Jul

Sep

Nov

Jan

Mar

May

Jul

Sep

Nov

Jan

Mar

May

Jul

Sep

dispensary 3

dispensary 2

dispensary 1

health centre 3

health centre 2

health centre 1

hospital 3

hospital 2

hospital 1

mRDT

2007 20082006

Quinine vials

Results 2: longitudinal study

Severe malaria

Give i.v quinine

Severe illness (NOT malaria)

• STOP antimalarials

• Continue with appropriate antibiotic

• Investigate for other causes of fever

• Repeat RDT and BS after 12-24hrs

Admission

Give immediately antimalarial and antibiotic

DANGER SIGNS

Perform RDT or BS

Uncomplicated malaria

Give antimalarial

Febrile illness(NOT malaria)

• Do NOT give

antimalarial

• Invest. for other

causes of fever

Do NOT

perform a

malaria test

NO

YES

NO

YES

Perform BS

+/- RDT

BS and RDT both

negatives

RDT and/or

BS positive

positive negative

Follow-up

PRIMARY AND SECONDARY LEVELPRIMARY LEVEL SECONDARY LEVEL

Refer the

patient

immediately

High malaria risk area

FEVER ANEMIA

Low malaria risk area

FEVER without an

obvious cause of fever ?

Suspected malaria case

NO

Antibiotic prescriptions in Dar es Salaam

Antibiotics

Antimalarials

� Proportion of febrile patients receiving:

D’Acremont et al, 2010, submitted

Before RDT implementation

After RDT implementation

49% 73%

81% 24%

But what are the causes of all these fevers

that are not malaria ?

?

8%

Study on etiologies of fever in children

To determine the etiology of fever

episodes in small children living in urban

and rural Tanzania

children 2 months - 10 yrs

temperature > 38°C

Methodology of the fever study

1005 patients

(507 in Dar es Salaam

and 498 in Ifakara)

Methodology

• Prospective study including children attending two outpatient

clinics (one urban and one rural) in Tanzania

• Inclusion criteria:

- aged 2 months - 10 yrs

- temperature > 38°C

• Full clinical assessment and investigations

based on pre-defined algorithms

• Computer-based diagnosis with levels of probability

• Real-time (RT-)PCR of naso-pharyngeal swabs for 13 viruses

• PCR and serologies on blood ongoing

All ARI50%

4%

12%

1%

5%

3%

20%

1%

3%

10%

31%

All gastroenteritis9%

Acute Resp. Infect.

URTI

Bronchiolitis

Non-doc. pneumonia

Doc. pneumonia

Gastroenteritis

amoeba

Rota/Adenovirus

Salmonella/Shigella

unknown etiology

Urine infection

Skin infection

Other

Sepsis due tobacteriemia

TyphoidMalaria

Unknown

Results 1: etiologies in all patients

All ARI38%

All gastroenteritis8%

Acute Resp. Infect.

URTI

Bronchiolitis

Non-doc. pneumonia

Doc. pneumonia

Gastroenteritis

amoeba

Rota/Adenovirus

Salmonella/Shigella

unknown etiology

Urine infection

Skin infection

Other

Sepsis due tobacteriemia

TyphoidMalaria

Unknown

5%

20%

2% 4%

6%

10%

36%

2%

7%

Results 2: etiologies in severe patients

Results 3: proportion of children infected with viruses

0%

20%

40%

60%

80%

100%

severe

pneumoniapneumonia URTI

unknown

fever

other

disease

any virus

any virus except PIC

Kenyan study (same

viruses)

Ref: Berkley JAMA 2010

86% 87%

82% 80%

64%

WHO definition

‘control

group’

Results 6: seasonality of influenza

0%

10%

20%

30%

40%

50%

Apr May Jun Jul Aug

FLUAV

FLUBV

0%

10%

20%

30%

40%

50%

Jul Aug Sep Oct Nov

Dar es Salaam

Ifakara

Development of improved practice guidelines for clinicians

Modified IMCI including

1. laboratory tools : malaria test, urine dipstick

2. additional clinical criteria: predictors for bacterial infections

(Acute Resp. Infect., typhoid)

Emphasis on rationale use of drugs (antimalarials and antibiotics)

Fever study: beyond the findings

Development of improved practice guidelines for clinicians

Modified IMCI including

1. laboratory tools : malaria test, urine dipstick

2. additional clinical criteria: predictors for bacterial infections

(Acute Resp. Infect., typhoid)

Emphasis on rationale use of drugs (antimalarials and antibiotics)

Fever study: beyond the findings

The e-IMCI interface

Remerciements

DSM City Medical Office of Health, Tanzania

Judith Kahama (co-researcher)

Ndeniria Swai (research assistant)

Gerumana Mpawa (logistics and data entry)

Ministry of health and Welfare, Tanzania

Deo Mtasiwa (Chief Medical Officer)

Ifakara Health Institute, Tanzania

Hassan Mshinda (ex-director)

Amana and St Francis hospital, Tanzania

Willy Sangu and P. Kibatala (directors)

Swiss Tropical and Public Health Institute

Christian Lengeler & Blaise Genton

Hôpitaux Universitaires de Genève

Laurent Kaiser & Pascal Cherpillod

Support financier de la part du Fonds National de la Recherche Suisse

TDR fournis en grande partie par USAID/Tanzania sous President Malaria Initiative