Weekly Epidemiological Bulletin Republic of Integrated Disease Surveillance and Response (IDSR) W30| 25 – 31 July 2016

Highlights Special focus on measles • Completeness for weekly reporting was 39% for the nonconflict- affected states and 54% for the IDP sites. • Five suspect measles cases were reported from Tonj South ! (3 cases & one death) and Mayom (2 cases). (Table 4.1). • Malaria is the top cause of morbidity in IDPs and nonconflict-affected areas. Status: Urgent • After securing reagents, testing is underway in the National measles laboratory for all the pending suspect measles • Malaria cases in the greater Northern Bahr el Ghazal and greater samples. Warrap exceeded expected levels in the week. Measles • Since the beginning of 2016, a total of 1,580 measles cases • Cholera transmission has leveled off in Juba and declined in Duk including at least 18 deaths (CFR 1.14%) have been and Terekeka. reported countrywide. Measles outbreaks have been Malaria confirmed in 12 counties. • During the week, malaria was the leading cause of mortality in IDPs. Acute Jaundice • A countrywide measles follow up campaign is planned for Syndrome November 2016. Public Health Priorities Early Warning, Alert and Response Neonatal Tetanus Figure 1a | IDSR Proportional morbidity WK 30 2016 Active responses

6% AWD Cholera Malaria 1% ABD Status: Warning 35% Measles Malaria Hepatitis E Virus 0.006% ! 69% Measles Measles Active alerts: Others Malaria

Figure 1b | Proportional morbidity in IDPs W30 2016 Event! based surveillance WK30 of 2016 Acute Jaundice Measles • 10 counties in Imatong state (4), Namorunyang state (4), and Syndrome 0% Malaria (2) submitted event log data in week 30. Two 34% 30% suspect measles cases were reported from Bagari county. ARI Samples have been shipped to Juba for testing. Neonatal Tetanus AWD 2% 27% Figure 1c | IDSR Completeness by county in WK30 2016 7% ABD Status: Warning

Other Manyo 10% Payinjiar 11% Aweil North 18% Melut 20% Fashoda 20% Magwi 21% System performance Terekeka 23% Wau 28% Completeness for weekly reporting was 39% for the Malakal 31% 31% non-conflict affected states and 54% for the IDP Yei 33% sites (Table 1). Aweil Centre 36% Twic Mayardit 36% National 39% South Sudan | 28 Sep 2015 Nine counties attained 100% completeness in Duk 40% Cholera Kapoeta East 44% reporting. Overall, 18 counties attained Raga 47% completeness of at least 80% (Figures 1c). Tonj North 50% Maiwut 50% Mayom 63% Timeliness for weekly reporting remains very low (11- Mundri West 63% 52%) for both the non-conflict affected states and IDP Kapoeta South 67% Aweil East 68% sites (Table 1). Tambura 68% Bor South 69% Abyei 70% Cumulative completeness reporting rate for 2016 is Mundri East 71% 41% for the non-conflict affected states and 85% for Nzara 75% Nagero 75% the IDP sites (Table 1). Yambio 77% Jur River 78% Table 1 | Surveillance performance in South Sudan as of Rumbek East 80% Mvolo 82% WK30 2016 Ezo 82% Rumbek Centre 85% Total Timelines Completeness Timeliness Completeness Maridi 88% System Facilities in week 30 of 2016 Cumulative for 2016 Aweil West 89% Aweil South 90% IDSR 1392 149(11%) 543(39%) 377(27%) 576(41%) Ibba 92% EWARN 48 25 (52%) 26 (54%) 29 (60%) 41 (85%) Longochuk 92% Tonj South 100% Gogrial East 100% Guit 100% The low reporting rates are attributed to the security tension in different Abiemnhom 100% parts of the country and partners evacuating non-critical staff. Yirol East 100% Rumbek North 100% Cueibet 100% Maban 100% Mayendit 100% 0% 20% 40% 60% 80% 100% 120% Completeness % IDSR and EWARN Reporting Performance by Partner and County in 2016 Table 2 | Reporting Performance [Timeliness and Completeness] by Partner and County as of WK30 2016

IDSR WK30 2016 Partner Number of health facilities No. Silent Counties WK30 2016 Completeness Timeliness

# # % # % 1. Juba COSV 1 0 0% 0 0% 2. Kajo-keji GOAL 2 2 100% 2 100% 3. Lainya HLSS 3 2 67% 2 67% Morobo IMA 5 0 0% 0 0% 4. IMC 7 3 86% 3 86% 5. Budi IOM 13 8 62% 0 0% 6. Ikotos IRC 2 0 0% 0 0% 7. Kapoeta North Medair 2 2 100% 2 100% Lafon MSF-E 2 0 0% 0 0% 8. MSF-H 6 2 33% 2 33% 9. Awerial SMC 5 5 100% 5 100% 10. Wulu UNIDO 6 4 67% 2 33% 11. Yirol West UNKEA 2 2 100% 2 100% Tonj East World Relief 1 1 100% 1 100% 12.

13 (25%) hospitals, 117 (36%) PHCCs, and 413 (41%) PHCUs in The 26 health facilities in the IDPs that did not submit their reports 35 counties of the nonconflict-affected states submitted their IDSR in week 25 are supported by HLSS, COSV, IRC, IMA, IMC, IOM, reports (Table 2). MSF-E, MSF-H, and, UNIDO (Table 2).

A total of 12 counties in the nonconflict-affected states did not submit any report in the reporting week (Table 2). The best performing partner-supported facilities during the week were GOAL, MedAir, UNKEA, and World Relief. 26 partner-supported health facilities in the conflict-affected states did not submit their reports in the reporting week (Table 2).

Trends for top causes of Morbidity Table 4 | Top causes of morbidity in 2015 and 2016 Consultations Table 3 | Consultations in South Sudan as of WK30 2016 New cases WK30 Cumulative cases as at WK30 System Disease ! 2015 2016 2015 2016 Consultations in week 30 of 2016 Cumulative consultations for 2016 Surveillance Malaria 41,309 124,002 846,972 939,002 System AWD 7,293 10,848 237,665 231,198 <5 years ≥5 years Total <5 years ≥5 years Total Meningitis 0 4 33 21 IDSR IDSR 39,103 60,857 99,960 880,349 1,452,008 2,332,357 ABD 1,143 1,674 51,346 41,260 Measles 12 10 378 551 EWARN 15,617 757,013 AJS 3 0 45 48 Total 115,577 3,089,370 Malaria 9,203 4,653 113,813 168,156 AWD 2,356 1,161 62,346 76,845 ARI 6,853 4,275 119,496 172,623 EWARN ABD 297 242 8,499 9,094 Table 3 shows the total consultations in 2016. Measles 11 0 496 383 AJS 20 0 219 823 Meningitis 2 0 19 9

Malaria is the top cause of morbidity in the IDPs and in the nonconflict affected states (Figures 1a, 1b, 6a, 6b, Table 4).

Overall morbidity trends for 2014-2016

Figure 6a | IDSR priority disease morbidity trends W1 2016 to WK30 2016 Figure 6b | EWARN Priority Disease Proportionate Morbidity W52 2013 to WK30 2016

IDSR Priority Disease Morbidity trends from week 01 to 30 of 2016 80% 800 90 70% 700 80 60% 600 70 50% 60 500 50 40% 400 40 30% 300 30 Completeness (%) 20% 200 20

Percentage of all consultations 10% cases per 100,000 population 100 10 0% 05 31 0 0 - - 07 01 - - 1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 2014/2

Epidemiological week of reporting in 2015 2015 2016 %_Malaria %_ARI %_Measles %_AJS %_AWD %_ABD Completeness ABD Malaria Status: Urgent Malaria Malaria is the top cause of morbidity and accounted for 69% and 30% of the Figure 7 | IDSR malaria trends by week, 2014 - 2016 consultations in the nonconflict-affected states and IDP sites respectively 600 (Fig. 1a, 1b, 7, 9a-f, 10a-d). 500 The image part with As seen from Figs. 8a-f, the malaria cases in the greater Northern Bahr el 400 Ghazal and the greater Warrap exceeded expected levels. The trends in relationship ID rId2 other states are within the expected levels. However, low reporting rates may 300 was not found in the mask the actual trends. 200 file.

The malaria incidence in Bentiu PoC has declined over the past two weeks Cases per 100,000 Population 100 but still exceeds expected levels. In Mingkaman, the malaria trend is on the 0 risk and currently exceed expected levels. The trends in the rest of the IDP 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 sites were within expected levels (Figs. 10a-d). Epidemiological week of reporting 2014 2015 2016 In the week, 13 malaria deaths were reported from Yei (2), Rumbek Center (1), Yirol East (1), Aweil Center (1), Aweil East (1), Gogrial East (2) Tonj South (1), Akobo (1), Juba 3 (1), and Tongping UNMISS (1) (Tables 5, 6). Malaria trend by zone

Malaria Incidence for greater Western Bhar el Ghazal, week 01 to 30, 2016 Figure 8 |IDSR trends for malaria in greater Warrap, W01 to W30, 2016 1800

1000 1600 900 1400 800 700 1200 600 1000 500 800 400 600 300

cases per 100,000 400

200 cases per 100,000

100 200 0 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 0 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 Epidemiological week Epidemiological Week 2016 Third quartile 2012-2014 2016 Third quartile 2012-2014

Malaria

Figure 9 | IDSR trends for Malaria in greater Northern Bahr el Ghazal from IDSR Malaria trends for greater Central from week 1 to 30, 2016! week 01 to 30,2016 2000 800 700

600 1500 500

400 1000 300

200 500 cases per 100,000 cases per 100,000 100

0 0 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 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 Epidemiological week Epidemiological week 2016 Third quartile 2012-2014 2016 Third quartile 2012-2014

Malaria

IDSR trends for Malaria in grater Western Equatoria from week 01 to 30, 2016 IDSR Malaria trends for greater , week 1 - 30, 2015 800 700

700 600 600 500 500 400 400 300 300 cases per 100,000 200 200 cases per 100,000 100 100

0 0 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 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45 47 49 51 Epidemiological week Epidemiological week 2016 Third quartile 2011-2014 2016 Third quartile 2012-2014 Malaria in IDPs

Figure 10a | Malaria trend for IDPs in Bentiu PoC 2014 to 2016 Figure 10b | Malaria trend for IDPs in Malakal PoC 2014 1,000 800 to 2016

800 600 The image part with 600 relationship ID rId3 400 400 252 was not found in the 200 cases per 10,000 200 cases per 10,000 file. - - 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 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 Week of reporting Week of reporting incidence 2014 incidence 2015 incidence 2014 incidence 2015 Third quartile incidence 2016 Third quartile incidence 2016

Figure 10c | EWARN trends for Malaria in UN House PoC 2014 Figure 10d| EWARN trends for Malaria in Mingkaman, 2014 to 600 2015 to 2015 300

400 200

200 cases per 10,000 100 cases per 10,000

- - 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 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 Week of reporting Week of reporting incidence 2014 incidence 2015 incidence 2014 incidence 2015 Third quartile incidence 2016 Third quartile incidence 2016

!

Acute Respiratory Infection (ARI)

45% Figure 11b | ARI Incidence by IDP Site in W30 2016 Figure 11 | ARI trends in IDPs W1 2015 to W30 2016 70% 40% 60% 35% 50% 30% 40%

25% 30%

20% 20% 10% 15% 0% 10% Percent of all consultations

Percent of total consultations 5% IMC Site 1 SMC Malou 0% IMC Clinic 2 IMC Clinic 1 H Lankien PHCC -

01 03 05 07 09 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45 47 49 51 53 HLSS Site 2 PHCC UNIDO Bow PHCU World Relief PHCC UNKEA Jikmir PHCC UNIDO Majak PHCU HLSS Site 1 Hospital H Bentiu Town Clinic MSF Medair Abayok Clinic UNIDO Gandor PHCU Epidemiological week of reporting - UNKEA Mandeng PHCC Medair Wonthow Clinic GOAL Dethoma Camp 2 GOAL Koradar IDP clinic SMC Dorok Mobile Clinic SMC Padiet Mobile Clinic SMC Paktap Mobile Clinic MSF UNIDO Meer Mobile Clinic 2015 2016 SMC Ayueldit Mobile Clinic

In the IDPs, ARI registered the second highest proportionate morbidity of 27.4% as compared to 35% in week 30 of 2015 and Figure 11b shows ARI morbidity by IDP site in week 30 of 2016. 23% in week 29 of 2016 (Fig. 11). Acute watery diarrhoea (AWD) Figure 12 | IDSR AWD trends by week, 2014 - 2016

AWD is a common cause of morbidity that currently accounts for 120 6% and 7% consultations in the nonconflict-affected states and 100 IDP sites respectively (Fig. 1a, 1b). 80 The overall AWD incidence [cases per 100,000] in the reporting The image part with week was 89 in the nonconflict-affected areas with the greater 60 Western Equatoria (658) and the greater Lakes (97) being the relationship ID rId3 40 most affected (Fig. 12). was not found in the Cases per 100,000 Population 20 In the IDPs, AWD morbidity is lower when compared to the file. corresponding period of 2015 but higher when compared to 2014 0 (Fig. 13). 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 Epidemiological week of reporting

Figure 14 shows AWD morbidity by IDP site in week 30 of 2016. 2014 2015 2016

Acute watery diarrhoea (AWD)

30% Figure 14 | ARI Incidence by IDP Site in W30 2016 25% Figure 13 | AWD trends in IDPs W51 2013 to W30 2016 25%

20% 20% 15%

15% 10% 5% 10% 0%

5% IMC Site 1 SMC Malou IMC Clinic 1 IMC Clinic 2 Percent of all consultations H Lankien PHCC Percent of all consultations - HLSS Site 2 PHCC UNIDO Bow PHCU World Relief PHCC

0% UNKEA Jikmir PHCC UNIDO Majak PHCU HLSS Site 1 Hospital H Bentiu Town Clinic MSF Medair Abayok Clinic UNIDO Gandor PHCU 01 03 05 07 09 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45 47 49 51 53 - UNKEA Mandeng PHCC Medair Wonthow Clinic GOAL Dethoma Camp 2 GOAL Koradar IDP clinic SMC Dorok Mobile Clinic SMC Padiet Mobile Clinic SMC Paktap Mobile Clinic MSF UNIDO Meer Mobile Clinic SMC Ayueldit Mobile Clinic 2015 2016

Acute bloody diarrhoea (ABD)

Figure 15 | IDSR ABD trend by week, 2013 ! - 2016 ABD is a common cause of morbidity that currently accounts 25 for 1% and 2% of consultations in the non-conflict affected states and IDP sites respectively (Fig. 1a, 1b). 20

The overall ABD incidence [cases per 100,000] in the 15 reporting week was 14 in the non-conflict affected areas with the greater Western Equatoria (99) and the greater Lakes 10 (15) being the most affected (Fig. 15). 5

Among the IDPs, the current ABD burden is lower when Cases per 100,000 Population 0 compared to 2014 and 2015 (Fig. 16 and 17). 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 Epidemiological week of reporting Figure 17 shows the number of ABD cases by IDP clinic in 2014 2015 2016 week 30 of 2016.

Acute bloody diarrhoea (ABD)

4% Figure 17 | ABD Incidence by IDP Site in W302016 Figure 16 | ABD trends in IDPs W1 2015 to W30 2016 30% 4% 25%

3% 20%

3% 15%

2% 10%

2% 5%

1% Percent of all consultations … … 0% … 1% Percent of all consultations IOM Clinic Row Labels SMC Malou 0% IMC Clinic 2 IMC Clinic 1 H Yuai PHCU - H Leer Hospital -

010305070911131517192123252729313335373941434547495153 H Thonyor Clinic HLSS Site 2 PHCC - COSV Jiech PHCU MSF IOM Abayok Clinic World Relief PHCC UNIDO Maal PHCU UNKEA Jikmir PHCC UNIDO Duong PHCC HLSS Site 1 Hospital MSF SMC Pamote Mobile UNIDO Meer Mobile H Bentiu Town Clinic SMC Ayueldit Mobile Medair Abayok Clinic - MSF

2015 2016 Nile Hope Adok PHCU UNIDO Nyadong PHCU UNIDO Mayendit PHCC UNKEA Mandeng PHCC Medair Wonthow Clinic GOAL Dethoma Camp 2 GOAL Koradar IDP clinic SMC Paktap Mobile Clinic MSF Measles Fig. 18.1 Measles cases in Gogrial West, W3 to WK30, 2016 • Five suspect measles cases were reported from Tonj South (3 14 cases & one death) and Mayom (2 cases). (Table 4.1). 12 10 • After securing reagents, testing is underway in the National 8 measles laboratory for all the pending suspect measles samples. 6 • Since the beginning of 2016, a total of 1,580 measles cases 4 The image part with including at least 18 deaths (CFR 1.14%) have been reported Number of cases 2 relationship ID rId3 countrywide. Measles outbreaks have been confirmed in 12 0 counties. 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 was not found in the Epidemiological week of rash onset file. • A countrywide measles follow up campaign is planned for November 2016. Fig. 18.2 Measles cases in Wau, W1 to WK30, 2016 6

5

Table 4.1| Measles cases by location and status as at WK30 of 2016 4

New suspect Suspect cases in Confirmed Cases Samples tested Outbreak status in County cases WK30, 2016 2016 in 2016 in 2016 2016 3 Mangatain IDP 2 2 2 Confirmed UN House PoC 4 3 3 Confirmed 2 Juba 16 0 3 Alert Yei 7 0 0 Alert Number of cases 1 Lainya 2 0 0 Alert Magwi 23 7 Alert 0 Kapoeta South 9 0 0 Alert 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 Mingkaman 2 0 0 Alert Epidemiological week of rash onset Awerial 8 0 0 Alert Rumbek Center 4 2 4 Alert Rumbek East 1 0 0 Alert Yirol East 1 1 1 Alert Figure 18.3| Measles cases, Rubkona, W52 2015 to WK30 2016 Yirol West 66 5 5 Confirmed 32 Aweil West 79 13 13 Confirmed Aweil Center 5 4 4 Confirmed 28 Aweil East 9 3 3 Alert 24 Aweil South 18 1 3 Alert 20 Aweil North 130 2 2 Confirmed Abiemnhom 16 1 0 Alert 16 Guit 1 0 0 Alert 12

Mayendit 27 2 12 Confirmed Number of cases 8 Mayom 2 388 11 14 Confirmed Leer (Adok) 7 2 6 Confirmed 4 Rubkona 211 7 8 Confirmed 0 Renk 3 0 0 Alert 50515253 1 2 3 4 5 6 7 8 9 10111213141516171819202122232425262728 Maban 1 1 1 Alert Abyei 331 15 23 Confirmed 2015 2016 Epidemiological week of onset Gogrial East 1 Alert Gogrial West 54 2 4 Alert Twic 69 12 12 Confirmed Tonj South 3 (1) 38 0 0 Alert ! Wau 17 0 1 Alert Ibba 3 0 2 Alert Tambura 4 0 4 Alert Yambio 9 0 7 Alert Malakal PoC 3 1 1 Confirmed Bor South 7 0 0 Alert Bor PoC 3 0 0 Alert Measles 5(1) 1,580 88 145

Table 4.1| Trend of measles cases by age-group and week in Gogrial West, W1-W29, Table 4.2| Trend of measles cases by age-group and week in Wau, W2-W26, 2016 100% 2016 100% 1 1 1 3 80% 80% 1 1 2 1 3 60% 4 5 60% 1 2 1 1 1 1 1 3 2 1 1 1 1 1 2 7 4 40% 40% Cases[No] 1 Cases[No] 1 20% 1 20% 2 1 2 1 3 1 0% 0% 5 6 7 12 14 15 20 21 23 24 25 26 27 28 29 2 4 5 10 19 22 23 26 Epidemiological week of rash onset in 2016 Epidemiological week of rash onset in 2016 <1yrs 1-4yrs 5-9yrs 10-14years 15+yrs <1yrs 1-4yrs 5-9yrs 10-14years 15+yrs

Table 4.3| Trend of measles cases by age-group and week in Abyei, W1 to Table 4.4| Trend of measles cases by age-group and week in Rubkona, W1-W25, 2016 W24, 2016 100% 2 2 100% 2 4 2 1 2 2 3 3 1 1 1 2 1 2 3 1 2 7 6 2 1 11 1 7 5 1 80% 4 2 2 2 3 4 2 1 2 1 8 1 2 4 2 1 1 2 1 6 3 11 17 5 1 6 3 12 4 60% 14 1 1 7 7 4 3 2 1 1 1 1 17 4 3 3 2 1 1 50% 1 1 5 1 10 4 17 2 1 3 7 40% 3 Cases [No] 7 20 9 4 12 2 5 Cases[No] 14 2 1 7 1 6 9 8 4 1 2 1 20% 11 12 2 3 10 2 5 6 6 2 1 3 3 10 4 5 3 3 1 2 1 0% 1 0% 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 1 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 Epidemiological week of rash onset in 2016 Epidemiological week of rash onset in 2016 <1yr 1-4yrs 5-9yrs 10-14yrs 15+yrs <1yr. 1-4yrs 5-9yrs 10-14yrs. 15+yrs

Fig 4.1 to 4.4 show the trend of measles cases by age-group in Gogrial Measles outbreaks confirmed in 12 counties (Table 4.1) West, Wau, Abyei, and Rubkona. Suspect meningitis Torit – Eastern Equatoria Aweil – Northern Bahr el Ghazal No new suspect measles case reported in Nyong Payam in No new suspect meningitis cases reported in the week. Torit. Two suspect meningitis cases were reported in Aweil on 31 Since 5 January 2016, eight suspect cases of meningitis have May 2016. The image part with been reported from Torit in Eastern Equatoria. Since the meningitis A preventive vaccination has just been relationship ID rId2 Nyong Payam in is the most affected after conducted; case based investigations have been initiated for reporting 7 (100%) suspect cases. the two suspect cases and their contacts. was not found in the file. Four samples tested at the National Public Health Laboratory Case management, surveillance, and community (NPHL) were negative for bacterial meningitis. sensitization have been enhanced and are ongoing.

The weekly attack rates for Nyong Payam remain below the alert and action threshold for epidemic meningitis .

Hepatitis E Virus (HEV)

HEV is the commonest cause of acute jaundice syndrome1 with Figure 19 | HEV trends in Mingkaman, Bentiu & Lankien W10 2014 to W30 2016 cases confirmed in Mingkaman, Bentiu, Lankien, Guit, and Leer. 16 350 14 300 Bentiu PoC reported 32 new HEV cases in week 30 (Fig. 19). 12 250 10 Since the beginning of 2016, a total of 728 HEV cases have 200 8 been reported from Bentiu. 150 6 4 100 Since the beginning of the crisis, 2,975 HEV cases including 22 2 50 No. cases in Bentiu deaths (CFR 0.74%) reported in Bentiu; 158 cases including No, cases in other sites 0 2015-2016* SUMMARY by States (Using NID figures for population estimates)0 seven deaths (CFR 4.4%) in Mingkaman; 38 cases including 3 8 13 18 23 28 33 38 43 48 3 5 10 15 20 25 30 35 40 45 50 2 7 12 17 22 27 Lab indicators one death (CFR 2.6%) in Lankien; 3 confirmed HEV cases in (Pending lab cases excluded)

2014 Cases Polio cases2015 Pending Stool2016 Adequacy NPEV Sabin like

Melut; 3 HEV confirmed cases in Guit; and 1 HEV confirmed

Epidemiological week

Cases years

Polio Polio

case in Leer. - Awerial Lankien Bentiu (#) ERC NPAFP Rate NPAFP Polio Stool VDPV Percent Percent Cumulative Cumulative AFP Lab/CLT Lab/ITD Pending Pending Pending Pending Number Number Population <15 <15 Population Cases of the Week theof Week Cases Non adequacy Adequate Specimens

State Specimens

HEV transmission is currently reported in Bentiu PoC and Bentiu Compatible CENTRAL EQUATORIA 737148 23 23 - 0 0 0 0 0 3.12 23 22 96% 1 4.35% 2 8.70% Town and is largely propagated by the sub-optimal access to 1 This only applies to the current context of South Sudan EASTERN EQUATORIA 674008 53 53 - 0 0 0 0 0 7.86 53 52 98% 12 23% 1 2% safe water and sanitation. JONGLEI 982693 23 23 - 0 0 0 0 0 2.34 23 22 96% 8 35% 3 13% LAKES 791864 51 51 - 0 0 0 0 0 6.44 51 51 100% 6 12% 3 6%

NORTHERN BAHR EL 987309 35 34 - 1 0 0 0 0 3.44 35 31 89% 4 11% 2 6% GHAZAL Other diseases of public health importance Table. 4.2|AFP surveillance indicators as of week 30 of 2016 2015UNITY-2016* 864151SUMMARY 18 17by States- 0 (Using1 0NID 0figures 0 ! for2.08 population18 16 89% estimates) 3 17% 1 6%

UPPER NILE 895541 16 16 - 0 0 0 0 0 1.79 16 12 75% 5 Lab31% indicators 2 13% 2015

WARRAP 1456973 54 54 - 0 0 0 0 0 3.71 54 54 100% (Pending12 22% lab cases 4 excluded)7%

Cases Polio cases Pending Stool Adequacy NPEV Sabin like Acute Flaccid Paralysis | Suspected Polio

WESTERN BAHR EL

316372 20 20 - 0 0 0 0 0 6.32 20 17 85% 5 25% 0 0% GHAZAL

Cases years

Polio Polio -

WESTERN EQUATORIA 516397 38 38 - 0 0 0 0 0 7.36 38 (#) 38 100% 4 11% 3 8% ERC NPAFP Rate NPAFP Polio Stool During 2016, a cumulative of 183 AFP cases have been reported countrywide VDPV Percent Percent Cumulative Cumulative AFP Lab/CLT Lab/ITD Pending Pending Pending Pending Number Number Population <15 <15 Population Cases of the Week theof Week Cases Non adequacy Adequate Specimens

State 8222455 331 329 - 1 1 0 0 0 4.00 331 315 Specimens 95% 60 18% 21 18%

SOUTH SUDAN (2 new AFP cases in week 29 of 2016). Compatible CENTRAL CENTRAL EQUATORIA 737148 238 236 1- 0- 0- 02 0 0- 3.121.9 236 226 100%96% 12 4.35%29% 20 8.70%0% EASTERN EASTERN EQUATORIA 674008 2453 2253 0- 0- 0- 0 01 01 7.866.4 5324 5223 98%96% 122 23%8% 10 2%0% In 2016, the annualized non-Polio AFP (NPAFP) rate (cases per 100,000 JONGLEIJONGLEI 982693 2823 2723 - 0- 0- 01 0 0- 2.345.1 2328 2224 96%86% 89 35%32% 30 13%0% population children 0-14 years) is 4 per 100,000 population of children 0-14 LAKES 791864 51 51 - 0 0 0 0 0 6.44 51 51 100% 6 12% 3 6% LAKES 791864 27 25 0 - - 1 0 1 6.1 26 24 92% 3 12% 1 4% NORTHERN BAHR EL 987309 35 34 - 1 0 0 0 0 3.44 35 31 89% 4 11% 2 6% years (target ≥2 per 100,000 children 0-14 years). NORTHERNGHAZAL BAHR EL * 987309 14 12 0 - - 1 1 - 2.5 14 14 100% 2 14% 0 0% GHAZALUNITY 864151 18 17 - 0 1 0 0 0 2.08 18 16 89% 3 17% 1 6% UPPER NILE 895541 16 16 - 0 0 0 0 0 1.79 16 12 75% 5 31% 2 13% All states except Central Equatoria have attained the targeted NPAFP rate of 2015 UNITY 864151 12 9 1 - - 2 0 1 2.5 11 10 91% 2 17% 2 17% ≥2 per 100,000 children 0-14 years in 2016 (Fig. 19.1). The non-Polio UPPERWARRAP NILE 1456973895541 2054 1954 0- 0- 0- 0 0 01 3.714.0 5420 5413 100%65% 128 22%40% 42 7%10%

2016 WESTERN BAHR EL WARRAP 316372 20 20 - 0 0 0 0 0 6.32 20 17 85% 5 25% 0 0% Enterovirus (NPEV) isolation rate (a measure of the quality of the specimen GHAZAL 1456973 19 17 0 - - 2 0 - 2.3 19 19 100% 2 11% 1 5% WESTERN BAHR EL cold chain) is 20% in 2016 (target ≥10%). WESTERN EQUATORIA 316372516397 1038 1038 - 0- 0- 0 0 0- 7.365.7 3810 3810 100%100% 42 11%20% 31 8%10% SOUTHGHAZAL SUDAN 8222455 331 329 - 1 1 0 0 0 4.00 331 315 95% 60 18% 21 18% WESTERN CENTRAL EQUATORIA 516397737148 218 216 10 - - 20 0 -- 1.97.3 216 216 100%100% 24 29%19% 00 0%0% Stool adequacy was 92% in 2016, a rate that is higher than the target of EASTERN SOUTH EQUATORIA SUDAN 8222455674008 18324 16822 02 - - 09 12 14 6.44.0 17924 16423 96%92% 362 20%8% 07 0%4% JONGLEI 982693 28 27 - 1 0 - 28 24 86% 9 32% 0 0% ≥80%. - - 5.1 *As of epidemiological week 29/2016 LAKES 791864 27 25 0 - - 1 0 1 6.1 26 24 92% 3 12% 1 4% NORTHERN BAHR EL

* 987309 14 12 0 - - 1 1 - 2.5 14 14 100% 2 14% 0 0% GHAZAL UNITY 864151 12 9 1 - - 2 0 1 2.5 11 10 91% 2 17% 2 17% UPPER NILE 895541 20 19 0 - - 0 0 1 4.0 20 13 65% 8 40% 2 10% Viral Haemorrhagic2016 WARRAP 1456973 Fever19 17 0 - - 2 0 - 2.3 19 19 100% 2 11% 1 5% Guinea Worm | Dracunculiasis WESTERN BAHR EL 316372 10 10 - - - 0 0 - 5.7 10 10 100% 2 20% 1 10% GHAZAL No new suspect hemorrhagic WESTERN EQUATORIA 516397fever 21cases 21 0 reported- - 0from 0 Aweil- 7.3North 21 21. The100% cumulative4 19% 0 0% No new suspect Guinea worm case reported in the week. remains 55 suspect SOUTHVHF SUDAN cases8222455 including183 168 2 10- deaths- 9 (CFR2 4 184.0. 2179% ) 164reportd 92% 36since 20% 724 4% December 2015. Children were most afffected and accounted *Asfor of epidemiologicalmost cases week 29/2016 and The cash reward for reporting a Guinea worm case is now 5,000 SSP. deaths. There are no new deaths reported since 28 February 2016.

Most common case symptoms include: unexplained bleeding (epistaxis), fever, fatigue, vomiting, jaundice. There is no evidence of person-to-person transmission. Animal bites | Suspected rabies Mixed vectorborne VHF suspected.

No suspect rabies cases reported in the week. A total of 38 blood samples have been obtained from suspect cases and shipped for testing. Test results (PCR, PRNT, ELISA) from WHO CC laboratories in Uganda (UVRI), South Africa (NICD) and Senegal (IPD) were negative for Ebola, Marburg, CCHF, Rift Valley Fever, Yellow Fever, Zika, West Nile, and Arenaviruses; 5 samples tested positive for Onyong-nyong virus by PRNT; 3 samples were IgM positive for Chikungunya; and 1 IgM positive for Dengue at NICD. An additional 66 samples were collected during the follow up investigations (20-30 June 2016) but have not been shipped for testing. Cholera Figure 19.2 | Cholera Epidemic curve in as of 6 Aug 2016 Cholera transmission has leveled off in Juba and declined in Duk and Terekeka.

Table 4.2 summarizes the cases and deaths by county. The image part with As of 6 August 2016, a cumulative of 883 cholera cases including 22 deaths (10 facilities and 12 community) (CFR relationship ID rId3 2.49%) had been reported in South Sudan. was not found in the National and state level cholera taskforce committees are file. coordinating preparedness and response activities.

Table 4.2| Cholera cases and deaths by county as of 6 Aug 2016

Reporting sites Total cases Total Facility deaths Total community deaths Total deaths Juba County 808 5 4 9 Duk County 61 5 3 8 Terekeka 14 0 5 5

Total 816 10 12 22

! Mortality

Table 5 | Mortality from IDSR reports countrywide WK30 2016 Table 6 | Proportional mortality by cause of death in IDPs WK30 2016 Total Total AWD Measles Malaria Malaria cases cases Akobo Bentiu Juba 3 Tongping COUNTY ≥5yrs <5yrs <5yrs ≥5yrs Others <5yrs ≥5yrs Cause of Death by IDP Grand Proportionate The image part with site <5yrs <5yrs ≥5yrs <5yrs ≥5yrs <5yrs Total mortality [%] Yei 0 0 2 0 0 2 0 relationship ID rId3 Kapoeta East 0 0 0 0 1 0 1 Burns 1 1 5 Rumbek Centre 0 0 1 0 0 1 0 5 was not found in the Yirol East 0 0 0 1 0 0 1 Chronic diarrhoea 1 1 Aweil Centre 0 0 1 0 0 1 0 Drowned 1 1 5 file. Aweil East 0 0 1 0 0 1 0 Aweil North 0 0 0 0 1 1 0 Malaria 1 1 1 3 15 Abiemnhom 4 0 0 0 0 0 4 5 Gogrial East 0 0 2 1 0 2 1 Perinatal death 1 1 Tonj South 0 1 2 2 3 5 3 Shock 1 1 5 Twic Mayardit 0 0 0 2 0 0 2 Total deaths 4 1 9 6 5 13 12 Asthma 1 1 5

Chronic diseases 1 1 5 A total of 25 deaths were reported from the stable areas with 10 deaths attributed to malaria (Table 5). The AWD deaths in Tuberculosis 1 1 2 10 Abiemnhom need to the investigated. Bleeding from the cord 1 1 5 30 Among the IDPs, Akobo, Juba 3, Tongping UNMISS, and Unknown 6 6 Bentiu PoC submitted mortality data (Table 6). Malaria 1 1 5

Grand Total 1 4 11 2 1 1 20 100 This week, 20 deaths were reported including 15 (75%) in Bentiu PoC and 8 (40%) in children <5 years (Table 6). The Crude Mortality Rates [CMR] in all the IDP sites that submitted mortality data in week 30 of 2016 were below the emergency This week, malaria were the leading cause of mortality in IDPs. (Table 6). threshold of 1 death per 10,000 per day (Fig. 21). The other causes of mortality in the week included Tuberculosis and The U5MR in all the IDP sites that submitted mortality data in week 30 of 2016 were below the emergency threshold of 2 perinatal complications (Table 6). deaths per 10,000 per day (Fig. 20).

Note: Mortality rates are calculated for PoC sites only and are based on the latest available population data from OCHA. They are reported from line lists and should include community and facility-based deaths. However, due to rapid in/out migration from the PoC sites, and possible under-reporting of community-level deaths, they should be interpreted carefully.

Crude and under five mortality rates in IDPs !

Figure 21 | EWARN Crude Mortality Rate for W1 2015 to W30 of Figure 20 | EWARN U5MR by Site - W1 2015 to W30 of 2016 1.2 2.5 2016 1.0 2.0

1.5 0.8

1.0 0.6

0.5 0.4 deaths per 10,000 per day 0.0 0.2

deaths per 10,000 per day 1 4 7 10 13 16 19 22 25 28 31 34 37 40 43 46 49 52 2 5 8 11 14 17 20 23 26 29 0.0 2015 2016 1 4 7 10 13 16 19 22 25 28 31 34 37 40 43 46 49 52 2 5 8 11 14 17 20 23 26 29 Epidemiological week Bentiu Juba 3 Malakal Mingkaman 2015 Epidemiological week 2016 Melut Akobo Wau Shiluk Threshold Bentiu Juba 3 Malakal Mingkaman Melut Akobo Wau Shiluk Threshold

Overall mortality in 2016 Table 7 | Mortality by IDP site and cause of death W1 to WK30 2016 Since the beginning of 2016, a total 858 deaths have been reported from the IDP sites of which 333 (39%) Azar - were children under-5 years (Table 7). IDP site Acute watery diarrhoea Cancer GSW Heart Failure Hepatitis E Hypertension Kala Malaria Maternal death Measles Meningitis Perinatal death Pneumonia Rabies SAM Septicemia Septicemia Stroke TB/HIV/AIDS Others Grand Total Bentiu 17 1 7 8 5 1 42 1 9 1 11 34 4 59 3 58 224 485 Most of deaths occurred in Bentiu, Malakal and Juba 3 Juba 3 3 2 2 8 1 11 9 5 3 3 25 27 99 PoC (Table 7). Malakal 7 4 9 2 5 3 1 2 4 13 10 1 2 3 10 52 128 Melut 2 1 3 2 1 2 2 2 7 4 11 37 Since the beginning of 2016, TB/HIV/AIDS has Mingkaman 2 4 7 1 11 25 registered the highest proportionate mortality of 12.6% Akobo 3 2 1 1 13 2 4 2 2 17 47 (Table 7). Wau Shiluk 1 1 3 1 3 1 1 8 18 37 Grand Total 33 4 13 24 5 5 8 74 3 11 3 31 72 4 82 1 5 12 108 360 858 Proportion During 2016, commonest causes of death in U5s were ate severe pneumonia, medical complications of mortality [%] 3.8 0.5 1.5 2.8 0.6 0.6 0.9 8.6 0.3 1.3 0.3 3.6 8.4 0.5 9.6 0.1 0.6 1.4 12.6 42.0 100 malnutrition, severe malaria, and perinatal complications. Data sources

This bulletin presents disease trends from the Integrated Disease Surveillance and Response (IDSR) System and the Early Warning Alert and Disease Network (EWARN).

The respective data is submitted by public health facilities serving host communities (non-conflict affected states or non IDP sites) and partner-supported facilities serving internally displaced persons (IDP) in the Republic of South Sudan.

Editorial

Editorial: Dr. Thomas A. Ujjiga, Dr. Alice L. Igale, Dr. George W. Worri, Korsuk Scopus, Robert M. Lasu, Rose A. Dagama, Jane Pita, Louis Julu, Gabriel Waat, Dr. Lincoln Charimari, Dr. Allan M. Mpairwe, Dr. Joseph F. Wamala, Dr. John P. Rumunu

Acknowledgements Contact

MoH and WHO gratefully acknowledge the support For more information, please contact: of all MoH staff in the states, WHO Field Officers, Department of Epidemics, Preparedness and Response and implementing-health cluster partners in MoH Republic of South Sudan collecting and reporting the data used in this bulletin. Email: [email protected]

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This bulletin is produced by the Ministry of Health with technical support from the WHO

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