South Sudan

Annexes W3 2018 (Jan15 - Jan21)

Integrated Disease Surveillance andResponse (IDSR)

2

Contents

AccessandUtilization|Mapofconsultationsbycounty

Access and Utilisation

Slide 2 Map 1 Map of consultations by county (2018)

Indicator-based surveillance

Slide 3 Figure 1 Proportional mortality

Slide 4 Figure 2 Proportional morbidity

Slide 5 Figure 3 Trend in consultations and key diseases

Disease trends and maps

Malaria

Slide 6 Trend in malaria cases over time

Slide 7 Malaria maps and alert management

Acute Watery Diarrhoea (AWD)

Slide 8 Trend in AWD cases over time

Slide 9 AWD maps and alert management

Bloody diarrhoea

Slide 10 Trend in bloody diarrhoea cases over time

Slide 11 Bloody diarrhoea maps and alert management

Measles

Slide 12 Trend in measles cases over time

Slide 13 Measles maps and alert management

Sources of data

1. Weekly IDSR Reporting Form

2. Weekly EWARS Reporting Form

Contents

1 W2 2018 (Jan 08-Jan 14)

Map 1 | Map of total consultations by county (W3 2018)

Number of consultations

0 1 1,000 2,500 5,000

Hub W3 2018

South Sudan 109,696 312,678

Access and Utilisation | Map of consultations by county

2 W3 2018 (Jan 15-Jan 21)

Fashoda

Nyirol

Uror

Ayod

Rubkona

Mayendit

Panyijiar

Yirol West

LongechukFangak

Aweil Centre

Aweil SouthGogrial West

Aweil East

Ezo

Abyei

Nzara

Gogrial East

Pibor

Maiwut

Nagero

Mvolo

Wau

Canal PigiTwic

Morobo

Panyikang

Lopa Lafon

Kapoeta South

Kapoeta East

Kajo Keji

Kapoeta North

Maridi

Terekeka

Tonj South

Jur River

Akobo

Yambio

Pariang

Yirol East

Cueibet

Mundri East

Tonj East

Lainya

Tonj North

Abiemnhom

Mayom

Aweil North

YeiBudi

Magwi

Ulang

Aweil West

Twic EastRumbek Centre

Rumbek North

Manyo

Leer

Mundri West

Malakal

Luakpiny Nasir

TamburaWulu

Guit

Torit

Bor

Rumbek East

Juba

Ibba

Awerial

Pochalla

Koch

Baliet

Duk

Renk

Ikotos

Raja

Maban

Melut

Aweil 19,458 52,428

Bentiu 7,939 25,200

Bor 5,218 28,399

Juba 11,123 29,517

Kwajok 17,071 48,017

Malakal 7,462 21,296

Rumbek 17,236 46,309

Torit 4,110 9,355

Wau 7,447 18,833

Yambio 12,632

3

Proportionalmortality

Proportionalmorbidity

Figure 1 | Proportional mortality (2018)

Malaria

Acute Respiratory Infection

(ARI)

Acute Watery Diarrhoea

Bloody diarrhoea

Acute Jaundice Syndrome (AJS)

Measles

Other

Syndrome W3 2018

# deaths % mortality # deaths % mortality

Malaria 6 75.0% 29 80.6%

ARI 1 12.5% 2 5.6%

AWD 0 0.0% 2 5.6%

Bloodydiarrhoea

0 0.0% 0 0.0%

AJS 0 0.0% 0 0.0%

Measles 0 0.0% 1 2.8%

Other 1 12.5% 2 5.6%

Total deaths 8 100% 36 100%

Proportional mortality

3 W3 2018 (Jan 15-Jan 21)

Figure 2 | Proportional morbidity (2018)

Malaria

Acute Respiratory Infection

(ARI)

Acute Watery Diarrhoea

Bloody diarrhoea

Acute Jaundice Syndrome (AJS)

Measles

Other

Syndrome W3 2018

# cases % morbidity # cases % morbidity

Malaria 34,334 56.7% 97,220 53.8%

ARI 8,167 13.5% 27,099 15.0%

AWD 7,234 11.9% 21,835 12.1%

Bloodydiarrhoea

1,280 2.1% 3,375 1.9%

AJS 0 0.0% 3 0.0%

Measles 15 0.0% 37 0.0%

Other 9,555 15.8% 30,995 17.2%

Total cases 60,585 100% 180,564 100%

Proportional morbidity

4 W3 2018 (Jan 15-Jan 21)

4

Trendinconsultationsandkeydiseases

IDSRProportionatemorbiditytrends- inrelativelystablestates

In the relatively stable states, malaria is the top cause of morbidity accounting for 34.8% of the consultations in week 3 (representing a decline from 35.8% in week 1).

Figure 3 | Trend in total consultations and key diseases (W3)

Total consultations

Malaria

Acute Respiratory Infection (ARI)

Acute Watery Diarrhoea

Acute Jaundice Syndrome (AJS)

Measles

Trend in consultations and key diseases

5 W3 2018 (Jan 15-Jan 21)

Num

ber

W05 2

017

W09 2

017

W13 2

017

W18 2

017

W22 2

017

W26 2

017

W31 2

017

W35 2

017

W39 2

017

W44 2

017

W48 2

017

W01 2

018

0

25000

50000

75000

100000

125000

150000

175000

200000

0

20

40

60

80

100

120

140

160

0% 10% 20% 30% 40% 50% 60% 70%

1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45 47 49 51 1 3

2017 2018 Num

bero

fcon

sulta

tionsinTho

usan

ds

Morbidity%

Epidemiologicalweekofreportingin2017

Fig.1|IDSRProportionatemorbiditytrends,week1,2017to3,2018

Consultations Malaria ARI AWD ABD Measles

5

IDPProportionatemorbiditytrends- indisplacedpopulations

IDPProportionatemorbiditytrends- indisplacedpopulations

Among the IDPs, ARI and malaria accounted for 21.6% and 17.4% of consultations in week 3. The other significant causes of morbidity in the IDPs include AWD, skin diseases, and injuries.

The top causes of morbidity in the IDPs in 2018 include ARI, malaria, AWD, skin diseases, injuries, and ABD.

0

10,000

20,000

30,000

40,000

50,000

0%

10%

20%

30%

40%

50% 1 2 3 4 5 6 7 8 9 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 1 2 3

2017 2018

Consultatio

ns

%ofM

obidity

Epiweek2017to2018

Fig.2|IDPProportionatemorbiditytrends,week01,2017,toweek3,2018

Consultations Malaria ARI AWD ABD

17.4%

21.6%

7.9%

0.8% 0.00%

3.76%

0.00% 2.64%

0.0%

5.0%

10.0%

15.0%

20.0%

25.0%

Malaria ARI AWD ABD Measles Skindiseases GSW Injuries

Prop

ortio

natem

orbidity[%

]

CausesofmorbidityamongtheIDPsweeks3,2018

6

Malaria|Trendsovertime

Malaria|MapsandAlertManagement

Malaria | Trends over time

6 W3 2018 (Jan 15-Jan 21)

Figure 4a | Trend in number of cases over time (South Sudan)

0

20000

40000

60000

80000

100000

120000

Graph legend

2017

− · − · − · − − 2016

− − − − − − − 2015

· · · · · · · · · · 2014

97,220Cases

29Deaths

7Alerts

Key malaria indicators (2018) Figure 4b | % morbidity Figure 4c | Age breakdown

Jan Mar May Jul Sep Nov

Map 2 | Map of malaria cases by county (2017)

a. 2014 b. 2015

c. 2016 d. 2017

Malaria | Maps and Alert Management

7 W3 2018 (Jan 15-Jan 21)

Map 3 | Map of malaria alerts by county (2017)

Map legend

Number of malaria cases

0 1 10,000 20,000 50,000

Number of malaria alerts

0 1 10

Alert threshold

Twice the average number of cases

over the past 3 weeks. Source: IDSR

7Alerts

4Verified

0Low Risk

0Moderate Risk

0High Risk

0Very High Risk

Risk Assessment

7

Malaria|Trendsbycounty

MalariatrendsinselectIDPsites

Malariatrendsbycounty

-

2,000

4,000

6,000

8,000

10,000

12,000

14,000

16,000

Weeks

MalariatrendsforAweilEastCountyin2017

3rdQuartile C-sum 2017

-

500

1,000

1,500

2,000

2,500

3,000

3,500

4,000

Weeks

MalariatrendsforAweilNorthCountyin2017

3rdQuartile C-sum 2017

-

500

1,000

1,500

2,000

2,500

3,000

3,500

Weeks

MalariatrendsforAweilSouthCountyin2017

3rdQuartile C-sum 2017

-

500

1,000

1,500

2,000

2,500

Weeks

MalariatrendsforAwerialCountyin2017

3rdQuartile C-sum 2017

-

500

1,000

1,500

2,000

2,500

Weeks

MalariatrendsforYirolEastCountyin2017

3rdQuartile C-sum 2017

-

1,000

2,000

3,000

4,000

5,000

6,000

7,000

Weeks

MalariatrendsforYirolWestCountyin2017

3rdQuartile C-sum 2017

-

1,000

2,000

3,000

4,000

5,000

6,000

7,000

Weeks

MalariatrendsforYirolEastCountyin2017

3rdQuartile C-sum 2017

-

1,000

2,000

3,000

4,000

5,000

6,000

7,000

Weeks

MalariatrendsforAwerialCountyin2017

3rdQuartile C-sum 2017

Malaria trends returned to normal in thecounties that registered high transmissionduring the rain season

Malaria trends in select IDP sites

Malaria trends in four of the large IDP sites - Bentiu Poc; UN House Poc; Malakal PoC; and Renk are below the thirdquartile

-

10

20

30

40

50

60

70

1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45 47 49 51

Proportionatemorbidity%

EpiWeek

Figure10a|MalariatrendforIDPsinBentiuPoC2017

Thirdquartile Propmob 2017

- 10

20

30

40

50

60

70

80

1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45 47 49 51 53

Proportio

natemorbidity%

Weekofreporting

Figure10b|MalariatrendforIDPsinMalakalPoC,2017

Thirdquartile Propmob 2017

- 5

10

15

20

25

30

35

40

45

50

1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45 47 49 51

Proportionatemrobidity%

Epiweek

Figure10c|EWARNtrendsforMalariainUNHouse,2017

Thirdquartile Propmob 2017

- 5

10

15

20

25

30

35

40

45

50

1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45 47 49 51

Proportio

natem

orbidity%

Figure10d|EWARNtrendsforMalariainRenk,2017

Thirdquartile Propmob 2017

8

AcuteWateryDiarrhoea|Trendsovertime

AcuteWateryDiarrhoea|MapsandAlertManagement

Acute Watery Diarrhoea | Trends over time

8 W3 2018 (Jan 15-Jan 21)

Figure 5a | Trend in AWD cases over time (South Sudan)

0

5000

2500

7500

10000

12500

15000

17500

20000

Graph legend

2017

− · − · − · − − 2016

− − − − − − − 2015

· · · · · · · · · · 2014

21,835Cases

2Deaths

14Alerts

Key AWD indicators (2018) Figure 5b | % morbidity Figure 5c | Age breakdown

Jan Mar May Jul Sep Nov

Map 4 | Map of AWD cases by county (2017)

a. 2014 b. 2015

c. 2016 d. 2017

Acute Watery Diarrhoea | Maps and Alert Management

9 W3 2018 (Jan 15-Jan 21)

Map 5 | Map of AWD alerts by county (2017)

Map legend

Number of AWD cases

0 1 5,000 10,000 20,000

Number of AWD alerts

0 1 10

Alert threshold

Twice the average number of cases over

the past 3 weeks. Source: IDSR

14Alerts

4Verified

0Low Risk

0Moderate Risk

0High Risk

0Very High Risk

Risk Assessment

9

AcuteBloodyDiarrhoea|Trendsovertime

AcuteBloodyDiarrhoea|MapsandAlertManagement

Acute Bloody Diarrhoea | Trends over time

10 W3 2018 (Jan 15-Jan 21)

Figure 6a | Trend in bloody diarrhoea cases over time (South Sudan)

0

500

1000

1500

2000

2500

3000

3500

Graph legend

2017

− · − · − · − − 2016

− − − − − − − 2015

· · · · · · · · · · 2014

3,375Cases

0Deaths

20Alerts

Key bloody diarrhoea indicators (2018) Figure 6b | % morbidity Figure 6c | Age breakdown

Jan Mar May Jul Sep Nov

Map 6 | Map of bloody diarrhoea cases by county(2017)

a. 2014 b. 2015

c. 2016 d. 2017

Acute Bloody Diarrhoea | Maps and Alert Management

11 W3 2018 (Jan 15-Jan 21)

Map 7 | Map of bloody diarrhoea alerts by county (2017)

Map legend

Number of bloody diarrhoea cases

0 1 500 1,000 2,000

Number of alerts

0 1 10

Alert threshold

Twice the average number of cases over the

past 3 weeks. Source: IDSR

20Alerts

4Verified

0Low Risk

0Moderate Risk

0High Risk

0Very High Risk

Risk Assessment

10

Measles|Trendsovertime

Measles|MapsandAlertManagement

Since the beginning of 2018, at least 22 suspect measles cases including at least 1 death (CFR 4.5%) have been reported. Of these, 11 suspect cases have undergone measles case-based laboratory-backed investigation with 11 samples collected out of which 3 measles IgM positive cases have been reported.

Measles | Trends over time

12 W3 2018 (Jan 15-Jan 21)

Figure 7a | Trend in number of cases over time (South Sudan)

0

50

100

150

200

250

300

Graph legend

2017

− · − · − · − − 2016

− − − − − − − 2015

· · · · · · · · · · 2014

37Cases

1Deaths

13Alerts

Key measles indicators (2018) Figure 7b | % morbidity Figure 7c | Age breakdown

Jan Mar May Jul Sep Nov

Map 7 | Map of measles cases by county (2017)

a. 2014 b. 2015

c. 2016 d. 2017

Measles | Maps and Alert Management

13 W3 2018 (Jan 15-Jan 21)

Map 8 | Map of measles alerts by county (2017)

Map legend

Number of measles cases

0 1 50 100 250

Number of measles alerts

0 1 10

Alert threshold

1 case.

Source: IDSR

13Alerts

7Verified

0Low Risk

0Moderate Risk

0High Risk

0Very High Risk

Risk Assessment

11

AcuteFlaccidParalysis|SuspectedPolio

MortalityintheIDPs

By County 2016

2017

*As of epidemiological week 49/2017

In week 3, 2018, four new AFP cases were reported from Central Equatoria, Jonglei, Northern Bahr el Ghazal, and Lakes hubs. This brings the cumulative total for 2018 to eight (8) AFP cases.

During 2017, a cumulative of 387 AFP cases were reported countrywide. The annualized non-Polio AFP (NPAFP) rate (cases per 100,000 population children 0-14 years) in 2017 was 4.71 per 100,000 population of children 0-14 years (target ≥2 per 100,000 children 0-14 years).

Stool adequacy was 87% in 2017, a rate that is higher than the target of ≥80%.

Environmental surveillance ongoing sinceMay 2017; with 23 samples testingpositive for non-polio enterovirus.

Source: South Sudan Weekly AFPBulletin

By County 2016

2017

*As of epidemiological week 49/2017

Table 6 | Proportional mortality by cause of death in IDPs W3 2018

Among the IDPs, mortality data was received from UN House PoC in week 3.(Table 6). A total of 4 deaths were reported during the week. UN House PoCreported 4 (100%) deaths in the week. During the week, 0 (0%) deaths wererecorded among children <5 years in (Table 6).

The causes of death during week 3 are shown in Table 6.

CauseofDeathbyIDPsite

Juba3

Totaldeaths

Proportionatemortality

[%]≥5yrspneumonia 1 1 25

HIV/AIDS 1 1 25

TB 1 1 25

Pepticulcerdisease 1 1 25

Totaldeaths 4 4 100

12

MortalityintheIDPs- CrudeandUnderfivemortalityrates

MortalityintheIDPs- Overallmortalityin2018

The U5MR in all the IDP sites that submitted mortality data in week 3 of 2018 is below the emergency threshold of 2 deaths per 10,000 per day (Fig. 20).

The Crude Mortality Rates [CMR] in all the IDP sites that submittedmortality data in week 3 of 2018 were below the emergency thresholdof 1 death per 10,000 per day (Fig. 21).

Table 7 | Mortality by IDP site and cause of death as of W3, 2018

l A total of 29 deaths have been reported from the IDP sites in 2018Table 7.

l The top causes of mortality in the IDPs in 2018 are shown in Table 7.

0.0

0.5

1.0

1.5

2.0

2.5

1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45 47 49 51 1 3

2017 2018

deathsper10,000perd

ay

Epidemiological week

Figure20|EWARNU5MRbySite- W12017toW3of2018

Bentiu Juba3 Malakal Threshold WauPoC

0.0

0.2

0.4

0.6

0.8

1.0

1.2

1.4

1.6

1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45 47 49 51 1 3

2017 2018

deathsper10,000perd

ay

Epidemiological week

Figure21|EWARNCrudeMortalityRateforW12017toW3of2018

Bentiu Juba3 Malakal Melut

IDPsite Asthma

Can

cer

HeartFailure

Kala-Azar

LiverCirrhosis

Malaria

Men

ingitis

Perinataldeath

Pneu

monia

SAM

Sepsis

Shock

TB/H

IV

Trau

ma

HIV/A

IDS

TB

Unko

wn

LRTIBleed

ing

Acutewatery

diarrhoea

Pep

ticulcer

disease

GrandTotal

Bentiu 1 1 1 3 2 1 1 3 1 3 1 18Juba3 1 1 1 1 1 1 1 1 1 9Akobo 1 1 2GrandTotal 1 1 1 1 1 2 1 3 3 1 1 3 1 1 1 1 3 1 1 1 29Proportionatemortality[%] 3.4 3.4 3.4 3.4 3.4 6.9 3.4 10.3 10.3 3.4 3.4 10.3 3.4 3.4 3.4 3.4 10.3 3.4 3.4 3.4 100.0

Formorehelpandsupport,pleasecontact:

Dr.Pinyi Nyimol MawienDirectorGeneralPreventiveHealthServicesMinistryofHealthRepublicofSouthSudanTelephone:+211955604020

Dr.MathewTutMosesDirectorEmergencyPreparednessandResponse(EPR)MinistryofHealthRepublicofSouthSudanTelephone:+211955295257

Notes

WHOandtheMinistryofHealthgratefullyacknowledgehealthclusterandhealthpooledfund(HPF)partnerswhohavereportedthedatausedinthisbulletin.WewouldalsoliketothankECHOandUSAIDforprovidingfinancialsupport.

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