| Literature DB >> 31598664 |
Navit T Salzberg1, Kasthuri Sivalogan1, Quique Bassat2,3,4,5,6, Allan W Taylor7, Sunday Adedini8,9, Shams El Arifeen10, Nega Assefa11, Dianna M Blau7, Richard Chawana8,9, Carrie Jo Cain12, Kevin P Cain13, J Patrick Caneer14, Mischka Garel1, Emily S Gurley15,16, Reinhard Kaiser17, Karen L Kotloff18, Inacio Mandomando3,19, Timothy Morris14, Peter Nyamthimba Onyango20, Hossain M S Sazzad21,22, J Anthony G Scott23, Anna C Seale11,23,24, Antonio Sitoe3, Samba O Sow25, Milagritos D Tapia18, Ellen A Whitney26, Mary Claire Worrell7, Emily Zielinski-Gutierrez13, Shabir A Madhi8,9, Pratima L Raghunathan7, Jeffrey P Koplan1, Robert F Breiman1.
Abstract
Despite reductions over the past 2 decades, childhood mortality remains high in low- and middle-income countries in sub-Saharan Africa and South Asia. In these settings, children often die at home, without contact with the health system, and are neither accounted for, nor attributed with a cause of death. In addition, when cause of death determinations occur, they often use nonspecific methods. Consequently, findings from models currently utilized to build national and global estimates of causes of death are associated with substantial uncertainty. Higher-quality data would enable stakeholders to effectively target interventions for the leading causes of childhood mortality, a critical component to achieving the Sustainable Development Goals by eliminating preventable perinatal and childhood deaths. The Child Health and Mortality Prevention Surveillance (CHAMPS) Network tracks the causes of under-5 mortality and stillbirths at sites in sub-Saharan Africa and South Asia through comprehensive mortality surveillance, utilizing minimally invasive tissue sampling (MITS), postmortem laboratory and pathology testing, verbal autopsy, and clinical and demographic data. CHAMPS sites have established facility- and community-based mortality notification systems, which aim to report potentially eligible deaths, defined as under-5 deaths and stillbirths within a defined catchment area, within 24-36 hours so that MITS can be conducted quickly after death. Where MITS has been conducted, a final cause of death is determined by an expert review panel. Data on cause of death will be provided to local, national, and global stakeholders to inform strategies to reduce perinatal and childhood mortality in sub-Saharan Africa and South Asia.Entities:
Keywords: CHAMPS; child mortality; global health; surveillance
Mesh:
Year: 2019 PMID: 31598664 PMCID: PMC6785672 DOI: 10.1093/cid/ciz599
Source DB: PubMed Journal: Clin Infect Dis ISSN: 1058-4838 Impact factor: 9.079
Figure 1.Inclusion and exclusion criteria for minimally invasive tissue sampling (MITS) and non-MITS enrollment. aA small proportion of confirmed Child Health and Mortality Prevention Surveillance (CHAMPS) eligible deaths (ie, family was approached for eligibility screening and confirmed eligibility information) are not enrolled in CHAMPS due to parental nonconsent or loss to follow-up. bThe MITS timeframe may be extended up to 72 hours after death if body is refrigerated shortly after death. cCircumstances may prevent the MITS from being conducted after MITS consent has been obtained. In these infrequent cases, data collection aligns with non-MITS procedures. dHistology is conducted at the site and at the central pathology laboratory located at the US Centers for Disease Control and Prevention. Abbreviations: CHAMPS, Child Health and Mortality Prevention Surveillance; HIV, human immunodeficiency virus; MITS, minimally invasive tissue sampling; TB, tuberculosis; VA, verbal autopsy.
Figure 2.Overview of Child Health and Mortality Prevention Surveillance procedures. Abbreviations: CHAMPS, Child Health and Mortality Prevention Surveillance; DeCoDe, Determination of Cause of Death; ID, identifier; MITS, minimally invasive tissue sampling.
Figure 3.Map of Child Health and Mortality Prevention Surveillance sites. Abbreviation: CHAMPS, Child Health and Mortality Prevention Surveillance.
Selected Site Characteristics of Child Health and Mortality Prevention Surveillance Sites
| Characteristic | Mozambique | South Africa | Mali | Kenya | Bangladesh | Ethiopia | Sierra Leone |
|---|---|---|---|---|---|---|---|
| Catchment area(s) | Manhiça | Soweto (selected 8 clusters), Thembelihle and surrounding informal settlements | Bamako (Djicoroni Para and Banconi) | Siaya County (Karemo) and Kisumu (Manyatta) | Baliakandi and Faridpur (selected 6 subclusters) | Kersa and Harar | Makeni (Bombali Shebora and Bombali Siari chiefdoms) |
| Setting | Rural | Urban | Urban | Rural (Siaya); urban (Kisumu) | Rural (Baliakandi); mixed (Faridpur) | Rural (Kersa); urban (Harar) | Urban and rural |
| HDSS establishment year | 1996 | 2017 (will be fully established in 2019) | 2006 | 2007 (Siaya); 2016 (Kisumu) | 2017 (Baliakandi); no HDSS established (Faridpur) | 2007 (Kersa); 2012 (Harar) | No HDSS established (early planning phase; currently using census data) |
| Total population under surveillance (2017) | 186 000 | 123 225 (2018 HDSS) | 87 126 (Djicoroni Para); 139 684 (Banconi) (2018 HDSS) | 93 000 (Siaya); 72 000 (Kisumu) | 216 362 (Baliakandi); ~2 000 000 (Faridpur 6 subclusters) | 131 431 (Kersa); 50 000 (Harar) | 161 383 |
| Population density | 81/km2 | 6400/km2 | 17 709/km2 (Djicoroni Para); 22 421/km2 (Banconi) | 359/km2 (Siaya); est. 10 000/km2 (Kisumu) | 894/km2 (Baliakandi); 1114/km2 (Faridpur 6 subclusters) | 372/km2 (Kersa); 1244/km2 (Harar) | 7521/km2; (Makeni City); 139.6/km2 (Bombali Shebora); no data for Bombali Siari alone |
| Under-5 population (2017) | 26 425 | 12 962 | 13 631 (Djicoroni Para); 24 450 (Banconi) (2018 HDSS) | 12 090 (Siaya); 11 700 (Kisumu) | 20 180 (Baliakandi); ~180 000 (Faridpur 6 subclusters) | 15 751 (Kersa); 4283 (Harar) | 22 247 |
| Government stakeholders | Instituto Nacional De Saúde (National Institute of Health) | Ministry appointed Committee for Morbidity and Mortality in Children, Gauteng Department of Health District Health Team; NICD | Ministry of Heath; INSTAT | Siaya and Kisumu county departments of health; Ministry of Health | Institute of Epidemiology, Disease Control, and Research; Ministry of Health and Social Welfare | Ethiopian Public Health Institute; Ministry of Heath | National Public Health Agency, currently under development; Sierra Leone Ministry of Health and Sanitation |
| Primary research partner(s) | Manhiça Health Research Centre; Barcelona Institute for Global Health (ISGlobal) | University of Witwatersrand; Medical Research Council: RMPRU | Center for Vaccine Development, University of Maryland, Baltimore | CDC Kenya; Kisumu County Department of Health; KEMRI | icddr,b; Bangabandhu Sheikh Mujib Medical University | Haramaya University; London School of Hygiene and Tropical Medicine | CDC–Sierra Leone; ICAP Columbia University; Focus 1000; World Hope International |
Abbreviations: CDC, Centers for Disease Control and Prevention; est., estimated; HDSS, health and demographic surveillance system; INSTAT, Institut National de la Statistique (National Institute of Statistics); KEMRI, Kenya Medical Research Institute; NICD, National Institute for Communicable Diseases; RMPRU, Respiratory and Meningeal Pathogens Research Unit.
Call-Center Notification Systems
| Faridpur/Baliakandi, Bangladesh | Bombali Shebora/Bombali Siari, Sierra Leone |
|---|---|
| The Bangladesh CHAMPS site developed a toll-free physician call center, partnering with MIAKI Media Ltd, to increase death reporting and also provide a service to the community. Through widely distributed health information materials, community members are instructed to call the center if they experience complications with pregnancy, child illness, or a medical emergency or would like newborn health advice. In case of illness, physicians discuss symptoms with callers to ascertain if there are any danger signs that require immediate referral to 1 of 6 designated health facilities. Community members are also instructed to call the center for reporting of births and child deaths. If a child mortality or stillbirth event is reported, relevant information is documented and communicated to the CHAMPS team. In addition to providing a platform for community death reporting, this system also enhances community access to physician consultation and improves the community’s abilities to make informed healthcare-seeking decisions. | The Sierra Leone CHAMPS site utilizes an existing toll-free call center to increase community-wide death reporting. The national emergency call system (known by its phone number, 117) was established in 2012 as part of a support system to improve maternal and child health and scaled up during the 2014–2016 Ebola outbreak for reporting all deaths and suspected cases of Ebola. Health providers and community members are instructed to call 117 to report all deaths. While overall reporting of deaths to 117 dropped sharply following the end of the Ebola epidemic, CHAMPS facility and community reporters have been trained to report child deaths and stillbirths to the call center, thereby increasing the system’s utilization and strengthening its utility. Additionally, the CHAMPS sociol-behavioral science team has conducted extensive community engagement to encourage widespread community use of the call center, addressing stigmatization that exists around the call center as a result of the Ebola epidemic. As a result of such activity, the CHAMPS catchment area Bombali District has the highest numbers of notified deaths to 117 in the country. When a child mortality or stillbirth event from within the CHAMPS catchment area is reported, relevant information is documented and communicated to the CHAMPS team. As the current civil registration and vital statistics data collection is paper-based, the 117 system provides an opportunity for creating an electronic reporting of deaths for civil registration and mortality surveillance programs. |
Abbreviations: CHAMPS, Child Health and Mortality Prevention Surveillance.
Selected Mortality Surveillance Characteristics of Child Health and Mortality Prevention Surveillance Sites
| Characteristics | Mozambique | South Africa | Mali | Kenya | Bangladesh | Ethiopia | Sierra Leone |
|---|---|---|---|---|---|---|---|
| Mortality surveillance start datea | 5 Dec 2016 | 22 Dec 2016 (Soweto); 1 Mar 2018 (Thembelihle) | 1 Mar 2017 | 13 Sep 2017 (Siaya) and 24 May 2017 (Kisumu) | 20 Sep 2017 (Baliakandi); 1 Oct 2018 (Faridpur) | 4 Feb 2019 | 9 Oct 2017 |
| MITS start dateb | 9 Dec 2016 | 22 Dec 2016 | 8 Aug 2017c | 13 Sep 2017 (Siaya) and 24 May 2017 (Kisumu) | 3 Oct 2017 (Baliakandi); 10 Oct 2018 (Faridpur) | 4 Feb 2019 | 25 Feb 2019c |
| Phased death notificationsd | No | Yes | No | No | No | No | No |
| Phased MITS enrollmente | Yes | Yes | No | No | Yes | Yes | Yes |
| Surveillance setting (as of June 2019) | Facility and community | Facility and community | Facility and community | Facility and community (Kisumu); community (Siaya) | Facility (Faridpur and Baliakandi) | Facility and community | Facility (MITS and non-MITS) and community (non-MITS only) |
| Surveillance staff | Health facility staff, CHWs, key community leaders | Health facility staff, community undertakers | Health facility staff, religious leaders, cemetery guards, CHWs (including relais and HDSS field workers), midwives | Health facility staff, mortuary staff, HDSS community members, religious leaders, CHWs, TBAs, village chiefs | Physician call center, health facility staff, religious leaders, community volunteers | Health facility staff, HDSS field workers, community reporters (CHWs, religious leaders, | 117 call alert system, health facility staff, community reporters, mortuary staff |
| 24-h mortality surveillance (notifications) | Yes | Yes | Yes | Yes | Yes | Yes | Yes |
| 24-h consent and MITS | Yes | Yes | No | Yes | Yes | No | No |
| MITS facilities | Manhiça General Hospital; Hospital Rural de Xinavane | Chris Hani Baragwanath Academic Hospital | CVD-Mali Morgue | Jaramogi Oginga Odinga Teaching and Referral Hospital | Faridpur Medical College Hospital; Zahed Memorial Pediatrics Hospital; Baliakandi Upazila Health Complex | Hiwot Fana Hospital; Kersa Health Centre | Makeni Regional Hospital |
| Location of MITS procedure | Morgue | Morgue | Morgue | Morgue | MITS room in each hospital | Morgue and MITS room | Morgue |
| Family member allowed to view procedure | No | Yes | Yes | Yes | Yes | Yes | Yes |
| Complimentary studies | COMSA-Mozambique; CadMIA-Plus (Maputo) | … | … | Kenya Mortality Study | … | … | Social Autopsy Pilot; COMSA-Sierra Leone |
Abbreviations: CaDMIA, Cause of Death using Minimally Invasive Autopsies; CHW, community health worker; COMSA, Countrywide Mortality Surveillance for Action; HDSS, health and demographic surveillance system; CVD, Center for Vaccine Development; MITS, minimally invasive tissue sampling; TBA, traditional birth attendant.
aThe mortality surveillance start date is the date a site began collecting death notifications for Child Health and Mortality Prevention Surveillance network purposes.
bThe MITS start date is the date a site began conducting MITS.
cSite began conducting non-MITS first before conducting MITS.
dPhased death notifications indicates that a site began mortality surveillance in a facility setting prior to conducting mortality surveillance in a community setting.
ePhased MITS enrollment indicates that a site began conducting MITS initially on facility-based deaths prior to conducting MITS on deaths that occur in the community.
Child and Maternal Health Information Abstracted for Minimally Invasive Tissue Sampling (MITS) and Non-MITS Cases
| Form | Data Category |
|---|---|
| Child abstraction | Basic case information |
| Recent hospital encounters and hospitalization leading to death | |
| Physical examination | |
| Past medical history | |
| Birth history | |
| Immunization records | |
| Growth chart | |
| Child and maternal HIV and TB information | |
| Diagnostic information | |
| Clinical summarya | |
| Maternal abstractionb | Maternal demographic information |
| Antenatal clinic history | |
| Pregnancy, labor, and delivery | |
| Placenta and cord description | |
| Maternal laboratory testing and treatments | |
| Maternal medications | |
| Maternal transfusions | |
| Information of previous pregnancies and pregnancy outcomes | |
| Perinatal outcome and basic characteristics of the enrolled deceased child | |
| Maternal death information (if applicable) |
Abbreviations: HIV, human immunodeficiency virus; TB, tuberculosis.
aClinical summary may be transcribed directly from patient records (if available) or may be composed by clinically experienced abstractors based upon available clinical data.
bMaternal records related to the deceased enrolled child are abstracted.
Child Health and Mortality Prevention Surveillance as a Mechanism for Data to Action
| Soweto, South Africa | Manyatta, Kisumu County, Kenya |
|---|---|
| In South Africa, CHAMPS mortality surveillance was first launched in Chris Hani Baragwanath Hospital, a central hospital in Soweto. Based on initial DeCoDe data from these hospital-based cases, hospital-acquired infections were identified as a leading cause of neonatal mortality in that site. As a result, the South Africa CHAMPS team, in partnership with the United States CDC, led a critical appraisal of current facility infection prevention and control practices and subsequently, received a grant from the Bill & Melinda Gates Foundation to develop a package of interventions to mitigate against the risk of hospital infections. Additionally, based on the initial round of DeCoDe data, the site identified that approximately 20% of stillbirths in the South Africa site may be due to invasive bacterial infection of the fetus. This has led to increased sensitivity of facility-based obstetricians to the value in stillbirth investigation and has invigorated a research agenda aimed at addressing the burden of stillbirths in South Africa, a significant, yet largely ignored population. Through the review of data and evaluation of potential causes and mitigation factors, the CHAMPS South Africa site is ensuring that CHAMPS data will not only contribute toward a better understanding of child mortality but will also actively improve the overall health of its population. | The Kenya CHAMPS site, in collaboration with the Kisumu County MOH, recently established an HDSS system in Manyatta aimed at strengthening existing MOH surveillance by systematizing and improving documentation. Establishment of the HDSS included mapping of households and enumerating residents through a baseline survey that established a unique identifier for each individual. According to the MOH, the area covered by each CHV should include between 100 and 120 households. Mapping demonstrated that areas allocated to CHVs had significantly more households than previously thought; some had from 250 to 650 households and one CHV village had >800 households. The implications of the underestimation mean that CHVs only visited the first 100–120 households in their coverage area and stopped there, returning to the same households on subsequent visits. This impacts intervention planning since only a fraction of the population would potentially be reached. As an example, bed nets were distributed to households in Manyatta, yet many households reported not receiving one due to the underestimation of the need. Based on the information gathered through the HDSS mapping and enumeration, the coverage area allocated to each CHV was examined by Kisumu County MOH. The process of realigning the areas allocated to CHVs to conform to a maximum of 120 households and recruitment of additional CHVs is ongoing. The mapping and enumeration will allow CHAMPS to have an accurate denominator for calculating rates of under-5 mortality and also provide adequate coverage by CHVs for all the households. |
Abbreviations: CDC, Centers for Disease Control and Prevention; CHAMPS, Child Health and Mortality Prevention Surveillance; CHV, community health volunteer; DeCoDe, Determination of Causes of Death; HDSS, health and demographic surveillance system; MOH, Ministry of Health.
Selected Health Characteristics of Child Health and Mortality Prevention Surveillance Sites
| Characteristic | Mozambique | South Africa | Mali | Kenya | Bangladesh | Ethiopia | Sierra Leone |
|---|---|---|---|---|---|---|---|
| Mortality data at the time of site selectiona | |||||||
| U5MR (per 1000 live births) | 71 | 56 | 123 | 76.6 (Siaya) and 79 (Kisumu) | 50 (est.) (Baliakandi); unknown (Faridpur) | 81.9 (Kersa); 22 (Harar) | 156 |
| IMR (per 1000 live births) | 40.6 | 40 | 78 | 54 | 41 (Baliakandi); unknown (Faridpur) | 45 (Kersa); 11 (Harar) | 92 |
| NMR (per 1000 live births) | 15.6 | 21 | 40 | 39 | 30 (Baliakandi); unknown (Faridpur) | 26.2 (Kersa); 4.1 (Harar) | 39 |
| SBR (per 1000 third-trimester pregnancies) | Unknown | 23 | 28 | Unknown | 22 (Baliakandi); unknown (Faridpur) | 15.7 (Kersa); 4 (Harar) | 24.8 per 1000 live birthsb |
| MMR (per 100 000 live births) | 208 | 310 | 550 | 495 | Unknown | 365 | 1360c; 695.7d |
| HIV | |||||||
| Country HIV prevalence, age 15–49, % (year) | 13.2 (2015) | 18.9 (2017) | 1.2 (2017)e | 21 (Siaya, 2018); 16.3 (Kisumu, 2018) | <1 (2011) | 1.1 (2016) | 1.7 (2018) |
| Site HIV prevalence, age 15–49, % (year) | 39.7 (2012) | 10 (est.) | Unknown | Unknown | Unknown | Unknown | Unknown |
| HIV prevalence in women of reproductive age, % (year) | 30 | 29 | 1.6 (2017)e | 22.4 (Siaya, 2018); 17.4 (Kisumu, 2018)f | Unknown | Unknown | Unknown |
| Vertical mother-to-child transmission rate, % | 5 | 1 | Unknowng | Unknown | Unknown | Unknown | 12.7 |
| Malaria | |||||||
| Endemic malaria | Yes | No | Yes | Yes | No | No | Yes |
Abbreviations: est., estimated; HIV, human immunodeficiency virus; IMR, infant mortality rate; MMR, maternal mortality rate; NMR, neonatal mortality rate; SBR, stillbirth rate per 1000 births, unless otherwise indicated; U5MR, under-5 mortality rate.
aAll data are from the point of Child Health and Mortality Prevention Surveillance (CHAMPS) site selection (as reported by the site) in 2015 unless otherwise indicated.
bGBD 2016 Mortality Collaborators. Global, regional, and national under-5 mortality, adult mortality, age-specific mortality, and life expectancy, 1970–2016: a systematic analysis for the Global Burden of Disease Study 2016. Lancet 2017; 390:1084–150.
cWorld Health Organization. Trends in maternal mortality: 1990 to 2015. Available at:
dGlobal Burden of Disease Study. Global, regional, and national levels of maternal mortality, 1990–2015: a systematic analysis for the Global Burden of Disease Study 2015. Lancet 2016; 388:1775–812.
eJoint United Nations Programme on HIV/AIDS (UNAIDS). 2017 country factsheets, Mali. Available at: http://www.unaids.org/en/regionscountries/countries/mali.
fRate from Jaramogi Oginga Odinga Teaching and Referral Hospital in Kisumu, Kenya.
gBased on UNAIDS 2017 country factsheet for Mali, 31% of pregnant women living with HIV received antiretroviral therapy for the prevention of vertical transmission.