Adapting the Global Malaria Control Strategies to Humanitarian Crises

Up to 247-500 million infected each year (?)1 million deaths annually(?)

Natural disasters have also increased significantly since 1997 and malaria epidemics have escalated in Africa and Asia

• Flooding• Drought• Earthquakes• Volcanoes

I.E. NE Kenya Flooding 1997, 2006, 2008

Aceh, Indonesia – tsunami Dec 2004, Cyclone Nargis, Burma May 2008

CONFLICT

Since the end of the cold war old conflicts have scaled up and new ones emerged:

• Mid Asia: Afghanistan, Tajikistan & Azerbaijan, Iraq• West Pacific (Asia): East Timor, Burma & Indonesia• Africa: Angola, Brazzaville Congo, Zaire/DRC,

Mozambique, Burundi, Rwanda, Sudan, Ethiopia/Eritrea, Somalia, Chad, Liberia, Sierra Leone, Guinea, Ivory Coast,

• Europe: Bosnia, Kosova, Chechnya…….

62% OCCURRED IN AFRICA

Malaria is endemic in 87% of all conflicts to date

African Refugee Crisis

Isolated and epidemic risk

Tsunami & cyclones

31.7million refugees, IDPs and people of concern worldwide today, source UNHCR Feb, 2009.

……………without counting isolated and hosting communities across central Africa

1 in 3 malaria deaths occurs in acute or recovering Humanitarian Crises

Host country

Country of origin

Baseline CMR

Refugee CMR

Thailand '79 Cambodia 1.0 6.3

Somalia '80 Ethiopia 2.5 31.9

Congo/Zaire '94

Rwanda 2.0 60.0

MONTHLY CMR IN SELECTED REFUGEE POPULATIONS

CMR crude mortality rate (deaths/1000/months)

THE TOP 5 KILLERS IN HUMANITARIAN CRISIS:

• Diarrhoeal diseases

• Malaria • Measles• Pneumonia

• Malnutrition

INCREASED VULNERABILITY TO MALARIA IN HCs

People caught up in or displaced by conflict or natural crises:

• Poor shelter + increased exposure to insect bites• Poor sanitation increasing human/fly contact • Flooding increasing insect vector breeding • Poor nutrition and multiple infections decrease

capacity of human immune system• Heath services/workers capacity is usually very

poor• Access is a major challenge

THE EMERGENCY MALARIA CONTROL TOOL BOX?

Accurate diagnosis + Effective treatment

COMMUNITY EDUCATION + MOBIIZATION IS KEY

Total Population = est. >16,000,000

THE MISSING HEART OF AFRICA?

THE CENTRAL AFRICAN HUMANITARIAN NIGHTMARE

58,000 CAR refugees in S Chad

250,000 Darfur refugees

166,700 Chadian IDPs

766 869 Host Chadians

800,000 CAR pop. in direct conflict zone, IDP?

80,000 CAR refugees in Cameroon

EASTERN CHAD : DARFUR BORDER

In 2006 Goz Beida host population = 224.208; of which 167,000 are internally displaced

<5=44.841; pregnant women=11.210 + 35,000 refugees

Security = poor and deteriorating

GOZ BEIDA HEALTH SERVICES IN 2006

263Goz Beida District Hospital

0609 MoH Health Centres / 4 effectively Open and running

143Goz Amer camp clinic

153Djabal camp clinic

DoctorNon diploma Nurse

Diploma Nurse

Skills level and Number of PersonnelType of health facility

COOPI (Italian NGO) was responsible for supporting all MoH facilities and managed all refugee health facilities

GOZ REPORTED BURDEN OF MALARIA IN 2006

In 2006 Chadian’s had almost NO access to confirmatory diagnosis or NO access to effective treatment with artemisinin based therapies.

New national malaria control policy had yet to be rolled out anywhere.

Répartition des pathologies sur les consultations DS Goz Beida. Année 2006

22%

8%

11%

59%

Paludisme

IRA

Diarrhée

Autres

MENTOR’s STATEGY :

• FOCUS ON PROVIDING MALARIA CONTROL SERVICES TO YOUNG CHILDREN AND PREGNANT WOMEN

• Intensive capacity building of all health staff (re fugees camps and Chadian MoH facilities)

• Intensive training of NGOs (Coopi, Oxfam, others) a nd MoH partners supporting HFs

• Patient screening, differential clinical diagnosis, confirmatory malaria diagnosis using RDTs

• ACT treatment for uncomplicated malaria. • IM artemether pre referral and • IPT

• Standardised supply of all RDTs, and child doses (<13) of ACT, and IM artemether for malaria case management, plus SP for IPT

• In early 2007 as attacks by rebels from Sudan scale d up 157,000 of the Chadian host population were forced to flee their homes (IDPs) and live rough (e r).

• MENTOR proportionally scaled up support for the IDPs along with MSF and others

• Plus implemented a 100% coverage prevention campaign of LLINs (and targeted IRS)

MALARIA CASES IN TWO SUDANESE REFUGEE CAMPS

0

100

200

300

400

500

600

JAN MAR MAY JUI SEPT NOV

Cas de paludisme. Camp de Djabal. 2006

Palud presume palud confirme

Cas de paludisme. Camp de Djabal Année 2007

0

5

10

15

20

1 2 3 4 5 6 7 8 9 10 11 12

présumés confirmés

Nombre total des cas de paludismes sur l'année 2007 en fonction des cas confirmés.

DS Goz beida

0

200

400

600

800

1000

1200

JANV FEV MARS AVRIL MAI JUIN JUILL AOUT SEPT OCT NOV DEC

Nombre total paludisme paludismes confirmés

MALARIA CASES SEEN AT MOH HEALTH FACILITIES

Nombre de cas de paludisme au sein de la population Dar Sila 2008

0200400600800

1000120014001600

Janv

ier

Févr

ier

Mar

s

Avril

Mai

Juin

Juille

t

Août

Septe

mbr

eO

ctob

reNov

embr

eDéc

embr

ePaludisme confirmé

Paludisme présumé

Répartition des pathologies sur les consultations DS Goz Beida. Année 2006

22%

8%

11%

59%

Paludisme

IRA

Diarrhée

Autres

IMPACT ON MALARIA

Répartiton des pathologies sur les consultations DS Goz Beida. Année 2007

7%

10%

13%

70%

Paludisme

IRA

Diarrhée

Autres

MorbidityGoz Beida health district 2008

IRA24,26%

Autres59,06% Diarrhé

12,76%

Malaria3,93%

By 2008 expanded from 6 to 13 health facilities to reach the IDPs

Abéché Health District

18%

15%

11%

56%

Malaria

RespiratoryInfection

Diarrhoea

Other

CENTRAL AFRICAN REPUBLIC

• TOTAL POPULATION: 3.7 M

• CONFLICT ZONES: OUHAM + OUHAM PENDE

• Conflict Zone Population: 800,000

• 58,000 Refugees in Southern Chad

• 80,000 Refugees in Cameroon

WORSTE AFFECTED: 200,000 living rough in forests around Paoua.

HEALTH FACILITIES = 8 (3 MSF supported)

Estimated pop. Access = 15-20%

100-200 Villages Burnt to the ground

WHAT WAS KNOWN ABOUT MALARIA BEFORE THIS?

Last reported malaria data for Central African Repu blic:Source: WHO GMP Global Malaria Data Base

95,644 suspected malaria cases nationally – 200353,134 < 5 yrs old42,510 > 5 yrs old % confirmed = zero/unknown

12,365 suspected malaria cases in Ouham - 200110,716 suspected malaria cases in Ouham Pende - 2001% confirmed = zero/unknown

MENTOR’S STRATEGY IN NORTHERN CAR:

• FOCUS ON PROVIDING MALARIA CONTROL SERVICES TO YOUNG CHILDREN AND PREGNANT WOMEN

• Intensive capacity building of all health staff in 8 functional facilities

• Establishment of a “Malaria Agent” network to reach the isolated conflict population – the 80%

• Large scale IRS of all households - >90% of 123,000 households

• Large scale community education – 200,000

Candidates are selected by their villages (to a set criteria) and sent for 4 days basic training: Signs and symptoms of simple and severe malaria

Diagnosis of malaria using RDTTreatment of uncomplicated + severe malaria at the community/home levelHow to manage fever and convulsion and referral

TRAINING + RE TRAINING OF MALARIA AGENTS

GRADUATION FROM FOREST BASED SCHOOLING

91% Pass Rate Equipped: bikes, uniform and malaria aid bags (thermometer, RDTs, ACT, sup. AS, record sheets, and laminated job aids.

Return to serve own and neighboring forest communities

RETRAINING SESSIONS FOR MALARIA AGENTS

Malaria during pregnancy/IPT for pregnant womenPrevention of malaria, IRS + ITNsCommunity Participation and mobilization

More sessions to add in ORS, de-worming and Fr supplements

TAKING SERVICES TO THOSE WHO HAVE NON AND NO ACCESS

36 Malaria Agents

Serving up to 100 villages in remote, insecure and distant areas

Weekly supervision, collection of records and use RDTs plus re-equipping

MALARIA AGENT ACCESS TO PREGNANT WOMEN

0

100

200

300

400

500

600

700

May

-Jul

y

Aug

Sep

t

Oct

Nov

(F

ight

ing)

Dec Jan

Feb

Mar

ch

Apr

il

Tot

al

NU

MB

ER

PregnantWomantreated in their2nd to 3rd trimesterIPT (pregnantwomen)

MONTHLY MALARIA CASE TOTALS FOR 200,000 PEOPLE

0

2000

4000

6000

8000

10000

12000

14000

May

-July

AugSep

tOct

Nov (Figh

ting)

DecJa

nFeb

Mar

chApr

ilTot

al

Mal

aria

Cas

es

Confirmed

Presumed

0

10002000

30004000

5000

60007000

8000

May

-Jul

y

Aug

Sep

t

Oct

Nov

(F

ight

ing)

Dec Jan

Feb

Mar

ch

Apr

il

Mal

aria

Cas

es

Presumed

Confirmed

Dry season

Worms, Diarrhea, RTI

>80% had URTI and conjunctivitis in January

RDT CONFIRMED MALARIA CASES BY CHILD AGE

0500

100015002000250030003500400045005000

May

-Jul

y

Aug

Sep

t

Oct

Nov

(F

ight

ing)

Dec Jan

Feb

Mar

ch

Apr

il

Tot

al

Con

firm

ed M

alar

ia C

ases

Confirmed

Children <5treated

6-15 yearstreated

Referral ofsevere cases

MALARIA CASES (ALL) BY GENDER

0

5001000

15002000

2500

30003500

4000

May

-Jul

y

Aug

Sep

t

Oct

Nov

(F

ight

ing)

Dec Jan

Feb

Mar

ch

Apr

il

ALL

MA

LAR

IA C

AS

ES

Male

Female

Mortality

85,534 MALARIA CASES IN 12 MONTHS

0

10000

20000

30000

40000

50000

60000

70000

80000

90000

Presumed Confirmed 1 Year Total

Mal

aria

Cas

es

85,534

34,370

51,164

ESTIMATING CAR’S REAL ANNUAL MALARIA CASE LOAD

Population = 3.7 million95,644 suspected malaria cases nationally – 2003Source: WHO GMP Global Malaria Data Base

• 85,534 suspected malaria cases amongst 200,000 peopl e• 34,370 RDT confirmed and treated by Malaria Agents• MSF report over 15,000 more confirmed at their faciliti es

• Does CAR have 3.7m/200,000 x 85,535 or 34,370

= 635,845 = 635,845 –– 1,582,397 (assuming similar transmission 1,582,397 (assuming similar transmission across similar geography)across similar geography)

CONSLUSIONS

1. CONFIRMATORY MALARIA DIAGNOSIS OF ALL CHLDREN PRIOR TO TREATMENT REDUCES THE BURDEN OF MALARIA

2. CONFIRMATORY DIAGNOSIS PRIOR TO TREATMENT CUTS WASTAGE OF ACT BY OVER 50%

3. RDTS ARE FESIBLE IN THE MOST RESORCE POOR SETTINGS

4. IF YOU CAN SUCEED IN CHAD AND CAR YOU CAN SUCCEED PERHAPS IN DR CONGO (THE HEART OF MALARIA? WITH 50 MILLION PEOPLE IN IT BUT LITTLE DATA)

1. MALARIA AGENT MODEL IS AN EFFECTIVE WAY OF IMPROVING ACCESS TO EFFECTIVE CASE MANAGEMENT AND IPT

2. RDTS ARE ESSENTIAL TO ENSURE MORE ACCURATE EPIDEMIOLOGICAL DATA SO WE CAN TRACK REAL DISEASE AND MEASURE REAL PROGRESS

3. LLIN DURABILITY HAS PROVED UNACCEPTABLY POOR IN EASTERN CHAD MAKING GREATER DEPENDANCY UPON DIAGNOSTIC AND CURRATIVE SERVICES

THANK YOU

MENTOR’s LLIN PROGRAMME AND STUDY – E. CHAD

EXTERNAL STUDY TO MEASURE COVERAGE, USAGE AND CONDITION OF 78 000 LLINs PROGRAMME

Objective: 100% coverage and usage by IDPs and host communities

LLINs distributed:400,00 Interceptor® LLINs26,000 Olyset® LLINs12,000Permanets t®)

Programme Steps:1. All LLINs were distributed between October 2007 – April 20082. All IDP and host families were assisted to hang the LLINs by the MENTOR

prevention team3. All communities received a standardised package of IEC theatre, posters

and radio messages prior to the distributions and during4. External surveys conducted Jan-February 2009 (dry season = Nov-June)

SUMMARY STUDY RESULTS

LLIN retention rates by subpopulation

88.2 - 95.6%92.7%IDP'sns

86.4 - 94.7%91.4%HOSTNets Retained

4.4 - 11.8%7.3%IDP'sns

5.3 - 13.6%8.6%HOSTNet Sold or Given Away

sig.95% CIfreq.

0.00055.2%71.1%Rainy Season

0.00043.7%67.7%Last NightOTHERS

ns86.4%85.8%Rainy Season

0.00059.2%71.5%Last NightPREGNANT WOMEN

ns98.5%99.4%Rainy Season

0.00080.0%85.8%Last Night<5

p <IDP'sHOST

Seasonal net cover rates of vulnerable groups:

USE OF LLINS BY SEASON

44.9 - 60.9%53.0%IDP'sns

51.8 - 66.4%59.3%HOSTSLEEP UNDER NET ALL YEAR ROUND

39.1 - 55.1%47.0%IDP's

ns

33.6 - 48.2%40.7%HOSTSLEEP UNDER NET DURING THE RAINY SEASON

p <95% CI% FREQ

LLIN MATERIAL CONDITION

Sampled net numbers = f (brands, status)

857431426Total

303195108Permanet

322133189Olyset

232103129Interceptor

TotalIDP'sHostsSubsamplesizes

Table 25: Dry season bednet usage = f (brands, status)

11%11%12%IDP’s ns

12%8%10%hostsunused

14%3%11%IDP’sns

8%1%3%hostsfishing

76%87%76%IDP’sns

80%91%87%hostssleeping

p<PermanetOlysetInterceptorDRY SEASON USE (percent)

MONTHLY HOLES > 5 MM BY LLIN BRAND