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COMMUNICATION BRIEF: KENYA NUTRITION SITUATION ARID AND SEMI-ARID AREAS LONG RAINS ASSESSMENT, JULY 2019

1.0. Key facts and messages

• According to the integrated Phase Classification conducted in July 2019, nutrition situation has deteriorated in

several counties (Figure 1).

• The high malnutrition levels are mainly due to food insecurity with low milk production and consumption and

increasing food prices observed in the most affected areas. This has resulted from the cumulative negative

effect of the below average 2018 short rains and the late on set of the 2019 long rains.

• High morbidity, limited access to health and nutrition services following scale down of integrated outreaches

in some areas, poor child practices coupled with pre-existing factors such as poverty, high illiteracy and poor

infrastructure have aggravated the problem.

• Though rains have been received in selected parts of ASAL counties, the effect of the rains on milk availability

will not be felt in the coming few months as animals will take time to breed as their body condition recover.

Acute malnutrition levels are therefore expected to remain high during the projection period (Figure 2).

• There is need to scale up interventions such as mass screening and integrated outreaches for early detection

and treatment of affected children and PLWs and to consider Blanket Supplementary Feeding Program in most

affected areas to prevent and mitigate the effects of acute malnutrition.

• The total number of children 6 to 59 months requiring treatment of acute malnutrition is 623,814 while 69,325

pregnant and lactating women require treatment (Table 1).

Figure 1: Current (LRA 2019) Nutrition Situation Map

Figure 2: Projected Nutrition Situation Map

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Table 1: Summary of total caseload and targets, July 2019

County Global Acute Malnutrition children

6 to 59 months

Severe Acute Malnutrition,

Children 6 to 59 Months

Moderate Acute Malnutrition,

Children 6 to 59 Months

Pregnant and Lactating Women

Total Caseload

Target Total caseload Target Total caseload

Target Total caseload

Target

ASAL 558,318 307,233 112,297 84,223 446,021 223,011 67,537 67,537

Urban 65,496 38,016 21,068 15,802 44,428 22,214 1,788 1,788

Grand Total 623,814 345,249 133,365 100,025 490,449 245,225 69,325 69,325

2.0. Situation Overview and Key drivers According to the Integrated Phase Classification for Acute Malnutrition conducted in July 2019, nutrition situation has deteriorated in several counties compared to February 2019 (Figure 1) with Laisamis, Turkana South and North being in extremely critical phase (Phase 5; GAM WHZ ≥30 percent). North Horr, Turkana Central and West, Mandera, Wajir, Garissa as well as Tiaty in Baringo County were in critical phase (Phase 4; GAM WHZ 15.0 - 29.9 percent) while West Pokot and Isiolo Counties were classified in serious phase (Phase 3; GAM WHZ 10.0 -14.9 percent). Saku, Moyale, Baringo North and South were in poor phase (Phase 2; GAM WHZ ≥ 5 to 9.9 percent) while Laikipia, Kitui, Narok, Kajiado, Taita Taveta, Kilifi, Kwale and Lamu were in acceptable phase (Phase 1; GAM WHZ <5 percent).

The high prevalence of acute malnutrition is mainly attributed to poor food availability with low milk production and consumption and increasing food prices observed in the most affected areas This has resulted from the cumulative negative effect of the below average 2018 short rains and the late on set of the 2019 long rains. High morbidity, limited access to health and nutrition services following scale down of integrated outreaches in some areas such as Laisamis in Marsabit, poor child practices coupled with pre-existing factors such as poverty, high illiteracy and poor infrastructure have aggravated the problem. Rains have been received in selected parts of ASAL counties such as Turkana and pasture has regenerated. However, the effect of the rains on milk availability will not be felt in the coming few months as animals will take time to breed as their body condition recover. In this regard, acute malnutrition levels are expected to remain high during the projection period (Figure 2).

3.0. Recommendation for action

• Strengthen community/health facility linkages and scale up community level activities such as active case finding, mass screening and integrated outreaches in the most affected areas for timely detection and treatment of acute malnutrition among children under five years and PLW

• Ensure nutrition commodities are available to manage the increased caseload

• Advocate for food sector response to bridge the food gap at household level

• Consider implementing Blanket Supplementary Feeding Program (BSFP) for areas with high levels of acute malnutrition to prevent and mitigate the effects of acute malnutrition

• Increase program performance monitoring, nutrition surveillance and scale up IMAM surge approach through existing partnerships for early warning, system capacity adjustment and early action

• Continue nutrition capacity strengthening for improved health and nutrition service delivery

• Promote and strengthen already existing multi-sectoral engagement and collaboration to ensure coordinated multi-sectoral efforts and synergy to address contributory factors of acute malnutrition across sectors

• Continued advocacy and inclusion of nutrition outcomes for under-fives as core indicators in agriculture, WASH, education, food security and social protection programs for concerted efforts and accountability to prevent and reduce vulnerability to acute malnutrition especially in arid areas

• Update contingency and response plans as part of early action and response

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4.0. Detailed number of children who are acutely malnourished and in need

of treatment The total number of children 6 to 59 months requiring treatment of acute malnutrition is 623,814 while 69,325 pregnant

and lactating women require treatment (Figure 3 and Table 2).

Figure 3: Estimated Caseloads for GAM and SAM, February 2019

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Table 2: Estimated Caseloads and targets; GAM, MAM and SAM

County Global Acute Malnutrition children 6

to 59 months

Severe Acute Malnutrition,

Children 6 to 59 Months

Moderate Acute Malnutrition, Children 6 to

59 Months

Pregnant and Lactating Women

Total Caseload

Target Total caseload

Target Total caseload

Target Total caseload

Target

Baringo 25,547 14,019 4,980 3,735 20,567 10,284 2,099 2,099

Embu 2,214 1,144 148 111 2,067 1,033 226 226

Garissa 45,139 24,079 6,036 4,527 39,103 19,552 4,620 4,620

Isiolo 8,487 4,648 1,617 1,212 6,871 3,435 1,524 1,524

Kajiado 24,974 13,608 4,482 3,362 20,491 10,246 3,702 3,702

Kilifi 25,555 14,583 7,222 5,417 18,333 9,166 431 431

Kitui 19,608 11,905 8,403 6,302 11,204 5,602 566 566

Kwale 15,498 8,844 4,380 3,285 11,118 5,559 954 954

Laikipia 14,892 7,912 1,862 1,396 13,031 6,515 1,503 1,503

Lamu 2,181 1,193 409 307 1,772 886 152 152

Machakos 4,860 2,912 2,184 5,352 2,676 216 216

Makueni 10,263 6,118 3,947 2,961 6,316 3,158 132 132

Mandera 91,704 50,039 16,750 12,562 74,954 37,477 12,216 12,216

Marsabit 28,225 15,521 5,635 4,226 22,590 11,295 6,480 6,480

Meru 10,047 5,573 2,198 1,648 7,849 3,924 909 909

Narok 23,251 12,110 1,938 1,453 21,313 10,657 474 474

Nyeri 1,389 719 99 74 1,289 645 112 112

Samburu 19,326 10,397 2,936 2,202 16,390 8,195 3,792 3,792

Taita Taveta 4,478 2,457 874 655 3,604 1,802 135 135

Tana River 20,604 11,207 3,620 2,715 16,984 8,492 1,848 1,848

Tharaka Nithi 1,570 871 343 258 1,226 613 134 134

Turkana 78,311 43,890 18,939 14,205 59,372 29,686 11,483 11,483

Wajir 43,810 23,708 7,213 5,409 36,597 18,299 9,912 9,912

West Pokot 32,983 17,830 5,356 4,017 27,626 13,813 3,916 3,916

ASAL 558,318 307,233 112,297 84,223 446,021 223,011 67,537 67,537

Kisumu 6,526 3,993 2,918 2,189 3,608 1,804 336 336

Mombasa 11,866 7,431 5,990 4,493 5,876 2,938 84 84

Nairobi 47,104 26,592 12,160 9,120 34,944 17,472 1,368 1,368

URBAN 65,496 38,016 21,068 15,802 44,428 22,214 1,788 1,788

GRAND TOTAL

623,814 345,249 133,365 100,025 490,449 245,225 69,325 69,325

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5.0. Process and Methodology Analysis during the workshop applied the global protocols for Integrated Phase Classification for Acute Malnutrition Version 3. A three days training was done to the analysis team on the protocols with continued technical support throughout the analysis and report writing process. Groups with experienced technical leads were formed to allow for peer support especially for new analysts and plenary sessions held to allow for further technical review, inputs and consensus. Data was gathered from multiple sources such as representative surveys, mass screening, routine data from the DHIS2, outbreak reports and the National Drought Management Authority sentinel surveillance. Only data of acceptable quality was used in the analysis. The analysis resulted to a current situation update and projection of the situation. Severity of acute malnutrition was referenced against international standards (Figure 4) and key contributing factors both food security and non-food security related factors were identified using the IPC for acute malnutrition conceptual framework (Figure 5) as laid out in the analysis work sheet. Since both IPCs were conducted simultaneously, results from the IPC for acute malnutrition were included Food Security analysis and results from Food Security IPC were also included in the IPC for acute malnutrition analysis. Finally, response actions and risk factors to monitor were identified.

Figure 4: IPC for Acute Malnutrition Reference Table

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Figure 5: IPC for acute Malnutrition Analytical Framework

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6.0. Acute Malnutrition Prevalence, June/July 2019

Areas Survey timing

GAM WHZ children 6 to

59 months

SAM WHZ children 6

to 59 months

GAM MUAC

children 6 to 59

months

SAM MUAC

children 6 to 59

months

PLW (%)

Plausibility score

Marsabit - Laisamis Jul-19 30.7 6.4 6.4 1.2 21.7 1

Marsabit North Horr

Jul-19 25.1 3.1 4.5 0.5 14.6 4

Marsabit - Moyale Jul-19 9 1.2 3.7 0.7 5.5 1

Marsabit - Saku Jul-19 9.5 1 0.9 0.5 2 9

West Pokot County Jun-19 11.7 1.9 3 0.2 3 2

Wajir County Jun-19 16.4 2.7 4.8 1.5 4.2 4

Turkana Central Jun-19 20.2 2.8 7.4 0.5 8.4 7

Turkana North Jun-19 30.2 7.4 11.4 1.7 9.8 7

Turkana South Jun-19 30.8 7.8 8.9 1.6 10.7 5

Turkana West Jun-19 23 5.7 11.4 3 7.2 0

Baringo (East Pokot)

Jul-19 20.9 3.5 8.1 0.8 6.8 3

Baringo (Baringo North Marigat)

Jul-19 9.3 2.3 3.4 1.1 1.5 3

Samburu County Jun-19 15.8 2.4 3.6 0.2 11.4 5

Garissa County Jun-19 17.2 2.3 6.1 0.9 4.2 5

Mandera County Jul-19 21.9 4 8.7 2.4 3.2 10

7.0. Summary of contributing factors

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PASTORAL NORTH EAST CLUSTER (TURKANA, MARSABIT, SAMBURU)

CONTRIBUTING FACTORS TURKANA NORTH

LAISAMIS NORTH HORR

TURKANA CENTRAL &

LOIMA MOYALE SAKU

TURKANA SOUTH

TURKANA WEST

SAMBURU

Inadequate dietary intake Minimum Dietary Diversity (MDD)

Minimum Meal Frequency (MMF)

Minimum Acceptable Diet (MAD)

Minimum Dietary Diversity – Women (MDD-W)

Others

Diseases Diarrhoea

Dysentery

Malaria

HIV/AIDS prevalence

Acute Respiratory Infection

Disease outbreak

Others

Inadequate access to food Outcome of the IPC for Acute Food Insecurity

analysis

Inadequate care for children Exclusive breastfeeding under 6 months

Continued breastfeeding at 1 year

Continued breastfeeding at 2 years

Introduction of solid, semi-solid or soft foods

Others

Insufficient health services & unhealthy environment

Measles vaccination

Polio vaccination

Vitamin A supplementation

Skilled birth attendance

Legend Major Contributing Factor Minor Contributing Factor No Contributing Factor No Data

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AGRO PASTORAL CLUSTER (KIENI, WEST POKOT, BARINGO, LAIKIPIA, NAROK AND KAJIADO COUNTIES)

CONTRIBUTING FACTORS BARINGO

(TIATY) KAJIADO KIENI NAROK LAIKIPIA

BARINGO

NORTH/

SOUTH

WEST POKOT

Inadequate

dietary intake Minimum Dietary Diversity (MDD)

Minimum Meal Frequency (MMF)

Minimum Acceptable Diet (MAD)

Minimum Dietary Diversity – Women (MDD-W)

Others

Diseases Diarrhoea

Dysentery

Malaria

HIV/AIDS prevalence

Acute Respiratory Infection

Disease outbreak

Others

Inadequate

access to food Outcome of the IPC for Acute Food Insecurity analysis

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Inadequate care

for children Exclusive breastfeeding under 6 months

Continued breastfeeding at 1 year

Continued breastfeeding at 2 years

Introduction of solid, semi-solid or soft foods

Others

Insufficient

health services &

unhealthy

environment

Measles vaccination

Polio vaccination

Vitamin A supplementation

Skilled birth attendance

Legend Major Contributing Factor Minor Contributing Factor No Contributing Factor No Data

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PASTORAL NORTH EAST CLUSTER (TANA RIVER, GARISSA, WAJIR, MANDERA AND ISIOLO COUNTIES)

CONTRIBUTING FACTORS WAJIR MANDERA TANA RIVER GARISSA ISIOLO

Inadequate dietary intake Minimum Dietary Diversity (MDD)

Minimum Meal Frequency (MMF)

Minimum Acceptable Diet (MAD)

Minimum Dietary Diversity – Women (MDD-W)

Others

Diseases Diarrhoea

Dysentery

Malaria

HIV/AIDS prevalence

Acute Respiratory Infection

Disease outbreak

Others

Inadequate access to food Outcome of the IPC for Acute Food Insecurity analysis

Inadequate care for children Exclusive breastfeeding under 6 months

Continued breastfeeding at 1 year

Continued breastfeeding at 2 years

Introduction of solid, semi-solid or soft foods

Others

Insufficient health services & unhealthy environment

Measles vaccination

Polio vaccination

Vitamin A supplementation

Skilled birth attendance

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COASTAL MARGINAL CLUSTER (KWALE, KILIFI, LAMU AND TAITA TAVETA COUNTIES)

CONTRIBUTORY FACTOR KWALE KILIFI LAMU TAITA TAVETA

Inadequate dietary intake

Minimum Dietary Diversity (MDD)

Minimum Meal Frequency (MMF)

Minimum Acceptable Diet (MAD)

Minimum Dietary Diversity – Women (MDD-W)

Others

Diseases Diarrhoea

Dysentery

Malaria

HIV/AIDS prevalence

Acute Respiratory Infection

Disease outbreak

Others

Inadequate access to food

Outcome of the IPC for Acute Food Insecurity analysis

Inadequate care for children

Exclusive breastfeeding under 6 months

Continued breastfeeding at 1 year

Continued breastfeeding at 2 years

Introduction of solid, semi-solid or soft foods

Others

Insufficient health services & unhealthy environment

Measles vaccination

Polio vaccination

Vitamin A supplementation

Skilled birth attendance

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SOUTH EAST MARGINAL CLUSTER (MERU NORTH, THARAKA, MBEERE, KUTUI, MAKUENI)

CONTRIBUTORY FACTORS MERU NORTH THARAKA MBEERE KITUI MAKUENI

Inadequate dietary intake Minimum Dietary Diversity (MDD)

Minimum Meal Frequency (MMF)

Minimum Acceptable Diet (MAD)

Minimum Dietary Diversity – Women (MDD-W)

Others

Diseases Diarrhoea

Dysentery

Malaria

HIV/AIDS prevalence

Acute Respiratory Infection

Disease outbreak

Others

Inadequate access to food Outcome of the IPC for Acute Food Insecurity

analysis

Inadequate care for children

Exclusive breastfeeding under 6 months

Continued breastfeeding at 1 year

Continued breastfeeding at 2 years

Introduction of solid, semi-solid or soft foods

Others

Measles vaccination

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Insufficient health services & unhealthy environment

Polio vaccination

Vitamin A supplementation

Skilled birth attendance

Legend Major Contributing Factor Minor Contributing Factor No Contributing Factor No Data

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