Journal of Global Health: Home Journal of Global Health
Watch: Survival: The Story of Global Health - FREE
JoGH Recommends:

Peer Review Conference



Creative Commons Licence
This work is licensed under a
Creative Commons Attribution
4.0 International License
.


Ivalda Macicame, Amílcar Magaço, Marta Cassocera, Celeste Amado, Américo Feriano, Sérgio Chicumbe, Jorge Jone, Quinhas Fernandes, Kátia Ngale, Emilia Vignola, Caroline De Schacht, and Timothy Roberton

Abstract

Background

As one of several countries that pledged to achieve the Millennium Development Goals (MDGs), Mozambique sought to reduce child, neonatal, and maternal mortality by two thirds by 2015. This study examines the impact of Mozambique’s efforts between 1997 and 2015, highlighting the increases in intervention coverage that contributed to saving the most lives.

Methods

A retrospective analysis of available household survey data was conducted using the Lives Saved Tool (LiST). Baseline mortality rates, cause-of-death distributions, and coverage of child, neonatal, and maternal interventions were entered as inputs. Changes in mortality rates, causes of death, and additional lives saved were calculated as results. Due to limited coverage data for the year 2015, we reported most results for the period 1997-2011. For 2011-2015 we reported additional lives saved for a subset of interventions. All analyses were performed at national and provincial level.

Results

Our modelled estimates show that increases in intervention coverage from 1997 to 2011 saved an additional 422 282 child lives (0-59 months), 85 450 neonatal lives (0-1 month), and 6528 maternal lives beyond those already being saved at baseline coverage levels in 1997. Malaria remained the leading cause of child mortality from 1997 to 2011; prematurity, asphyxia, and sepsis remained the leading causes of neonatal mortality; and hemorrhage remained the leading cause of maternal mortality. Interventions to reduce acute malnutrition and promote artemisinin-based combination therapy (ACT) for malaria were responsible for the largest number of additional child lives saved in the 1997-2011 period. Increases in coverage of delivery management were responsible for most additional newborn and maternal lives saved in both periods in Mozambique.

Conclusion

Mozambique has made impressive gains in reducing child mortality since 1997. Additional effort is needed to further reduce maternal and neonatal mortality in all provinces. More lives can be saved by continuing to increase coverage of existing health interventions and exploring new ways to reach underserved populations.


Like many sub-Saharan African countries, Mozambique made a commitment to achieve Millennium Development Goals (MDGs) 4 and 5: to reduce its under-five mortality rate (U5MR) by two thirds and its maternal mortality ratio (MMR) by three quarters by 2015 [1]. Results from Demographic and Health Surveys (DHS) in 1997, 2003, and 2011 suggest that Mozambique went a long way to achieving the U5MR target, but not the MMR target. The U5MR decreased from 201 in 1997 to 153 in 2003 and 97 in 2011 [2-4]. The MMR declined from 692 in 1997 to 408 in 2003, but then remained stagnant at 408 in 2011 [2-4].

In the coming years, the Mozambique Ministry of Health aims to “accelerate progress in reducing maternal and neonatal mortality” to achieve Sustainable Development Goals (SDGs) 3.1 and 3.2, as outlined in its Health Sector Strategic Framework (PESS) for 2014-2019 [5]. To successfully prioritize the scale-up of interventions during this next period, it will help to first explore which interventions were most impactful during the previous period. Understanding how the scale-up of interventions has contributed to saving lives in the past will help to set effective targets and expectations going forward.

The Lives Saved Tool (LiST) is a modelling program within the Spectrum software package that has been used in various settings to model the impact of coverage changes on child and maternal mortality [6,7]. Users enter custom input values for baseline mortality rates, cause-of-death distributions, disease incidence, and coverage rates. Outputs can be generated showing how increases in coverage prevent additional deaths over time, affecting mortality rates and causes of death [8]. The number of additional lives saved can be attributed to specific interventions, allowing users to see which interventions contributed the most to reducing deaths and improving population health.

As part of work undertaken with the National Evaluation Platform (NEP) in Mozambique, we conducted a retrospective LiST analysis to estimate the additional lives saved by changes in intervention coverage from 1997 to 2015. The NEP supports effective policy-making for child and maternal health, by conducting secondary analyses of national and provincial data and supplying policy-makers with evidence to inform decisions [9]. Our goal was to highlight the programmatic efforts in Mozambique that were most impactful in reducing child, neonatal, and maternal deaths from 1997 to 2015, so as to inform future efforts to achieve the SDGs and continue to improve the health of women and children throughout the country.

METHODS

Study design and data sources

In this retrospective secondary analysis, we modelled national and provincial changes in coverage of child and maternal health interventions between 1997 and 2015, and estimated the impact of those coverage changes on child, neonatal, and maternal mortality in Mozambique. Intervention coverage data were obtained from Demographic Health Surveys (DHS) in 1997, 2003, and 2011; a Multiple Indicator Cluster Survey (MICS) in 2008; an AIDS Indicator Survey (AIS) in 2009; and an Immunization, Malaria and HIV/AIDS Indicators Survey (IMASIDA) in 2015. These surveys represent all of the available household surveys with data on coverage of child and maternal health interventions in the past 20 years that are representative at national and provincial levels.

For national baseline child and neonatal mortality rates we used estimates from the UN Inter-agency Group for Child Mortality Estimation (UN IGME) [10]. For baseline maternal mortality rates we used published estimates from WHO, UNICEF, UNFPA, World Bank Group, and the UN Population Division [11]. We calculated provincial baseline mortality rates using national-to-subnational LiST projections to estimate provincial mortality rates based on differences in provincial coverage to national coverage.

The data sources for baseline cause-of-death estimates for Mozambique at national level were those used by LiST by default and come from WHO mortality estimates [12,13]. For provincial cause-of-death estimates, we created national-to-subnational LiST projections (as above) to estimate provincial cause-of-death estimates based on differences in provincial coverage to national coverage.

Data analysis

Of the 72 indicators with known effectiveness values that are customizable within LiST, we identified 55 indicators available in the Mozambique household survey data sets, including preventative and curative interventions during pregnancy, childbirth, the neonatal period, and childhood. We used raw survey data to recalculate certain indicators using the software STATA version 13 (Stata Corp, College Station, TX: StataCorp LP), so as to standardize indicators for comparison over time, and to match the indicator definitions expected by LiST. Additionally, we calculated proportions of children stunted and wasted by age category and Z-score, to accurately calculate the impact of interventions on children in different risk categories.

We undertook our analysis with LiST version 5.441 (Spectrum). We manually inputted survey coverage data for the years that were available, and linearly interpolated between these years. For indicators that were not available in survey data sets, or for which only one year of data was available, we flatlined coverage from 1997 to 2015 and these interventions thus had no effect on the model. For indicators where data was available for only two years, or was not available for either 1997 or 2015, we linearly interpolated coverage between the available years, and duplicated (flatlined) coverage before and after the available years.

Once the projections were complete, we used LiST to generate three types of outputs at national and provincial levels: mortality rates, number of deaths by cause, and number of additional lives saved by intervention. For each of these outputs we separated results by age category: neonatal (0-1 month), child (0-59 months), and maternal. Once we had calculated the additional lives saved for each intervention, we identified the 10 interventions that contributed the largest number of additional lives saved nationally, and listed the number and proportion of additional lives saved from the same interventions by province.

While we had data for most indicators for the years 1997, 2003, 2008, 2009, and 2011, we only had data for a limited number of indicators from the 2015 IMASIDA survey. Given that LiST relies on coverage data to calculate accurate results, the limited availability of 2015 data meant that LiST would underestimate the number of lives saved in the period 2011-2015. We therefore chose to present our findings in two time periods: 1997-2011 and 2011-2015. For 1997-2011 we reported all available results. For 2011-2015 we only reported additional lives saved for a subset of interventions.

RESULTS

Changes in coverage of interventions

The coverage values for child, neonatal, and maternal interventions that we used as inputs for our LiST projections are available in Table 1 (national coverage values for single-value indicators) and Appendices S1 & S2 in Online Supplementary Document(Online Supplementary Document) (breastfeeding, stunting, and wasting by age category; and provincial coverage values). While there were variations in coverage rates over time and across provinces, most interventions showed a general increase in coverage from 1997 onwards. Coverage of vaccines increased in all provinces of Mozambique from 1997 to 2011, and continued to increase in most provinces until 2015. Coverage of diphtheria-tetanus-pertussis vaccine 3 doses (DPT3) decreased in Tete between 2011 and 2015, and coverage of measles vaccine decreased in Nampula from 2011 to 2015. Coverage of oral rehydration solution (ORS) for diarrhea increased nationally from 1997 to 2011, but decreased in many provinces from 2011 to 2015. Coverage of pneumonia interventions increased steadily from 1997 to 2015. Coverage of malaria interventions increased nationally, although Maputo Province and Maputo City had low coverage of antimalarials in all years. Data from 1997 to 2015 showed consistent increases in coverage of maternal and neonatal interventions in 10 of the 11 provinces, with Manica showing decreasing coverage of antenatal care (ANC4), facility delivery, and skilled birth attendance from 2011 to 2015. All maternal interventions had higher coverage in the provinces from the southern region of Mozambique.

Table 1.  Intervention coverages at national level from 1997 to 2015
DHS DHS MICS AIS DHS IMASIDA
1997 2003 2008 2009 2011 2015
Preventive ITN/IRS 5.80% 26.17% 51.45%
Improved drinking water source 70.15% 83.15% 83.23% 89.00% 84.00%
Water channeled into the household 4.85% 5.26% 6.85% 6.01% 10.82%
Improved Sanitary Infrastructures 28.59% 39.40% 41.04% 41.74% 49.09%
Pregnancy Antenatalcare (ANC) 4 or more visits 40.77% 52.95% 48.44% 54.60%
Tetanus vaccine: 2+ doses during the most recent pregnancy 30.94% 58.68% 66.75% 66.26%
Intermittent and preventive treatment for malaria during pregnancy 44.10% 40.74% 20.35% 34.20%
Delivery Skilled birth attendant (births in 2 years before survey) 44.60% 49.89% 55.25% 55.99% 73.00%
Facility delivery 44.33% 50.91% 58.09% 58.86% 70.30%
Preventive Vitamin A in the last 6 months (6-59 months of age) 52.00% 71.99% 75.19%
Safe excretion of the child's stool 57.49% 56.93% 77.84%
Vaccine Received 3 doses of DPT 60.27% 72.73% 70.43% 77.02% 81.60%
Received measles vaccination 57.78% 76.83% 65.47% 81.58% 82.70%
Curative ORS for diarrhea 41.87% 48.65% 38.24% 55.08% 45.90%
Antibiotics for diarrhea 27.69%
Search for pneumonia care 38.54% 55.36% 59.07% 53.64% 56.50%
Antimalarials – Artemisinin compounds for malaria 6.20% 21.72% 22.52% 35.60%

ITN/IRS – Insecticide-treated nets/indoor residual spraying, ORS – oral rehydrationn salts, DPT – diphtheria, pertussis and tetanus

*Disaggregated coverage values for breastfeeding, stunting, and wasting by age category are shown in Appendices S1 & S2 in Online Supplementary Document(Online Supplementary Document). Provincial-level coverage values are also shown in Appendices S1 & S2 in Online Supplementary Document(Online Supplementary Document).



Changes in mortality

LiST estimates trends in mortality rates arising from changes in intervention coverage. Table 2 shows the mortality rates estimated by our projections. The national under-five mortality rate (U5MR) decreased from 196 in 1997 to 145 in 2011. The provinces in the northern region (Niassa, Cabo Delgado, Nampula) showed the greatest percentage reduction, while Maputo Province showed the smallest percentage reduction. The neonatal mortality rate (NMR) dropped from 50 in 1997 to 41 in 2011. Cabo Delgado was among the provinces with a high NMR in 1997 and its percentage reduction was only 7%. Maputo Province already had a low NMR in 1997, but showed one of the greatest reductions in mortality from 1997 to 2011. Gaza and Maputo City showed slight increases in NMR from 1997 to 2011. The national maternal mortality ratio (MMR) decreased from 870 in 1997 to 786 in 2011. Maputo Province showed the highest percentage reduction in MMR, while Maputo City showed a slight increase.

Table 2.  Changes in mortality and additional lives saved for children, newborns, and mothers from 1997 to 2011
Child (0-59 months) Neonatal (<1 months) Maternal
Under-5 mortality rate, 1997 Under-5 mortality rate, 2011 % reduction in mortality (1997-2011) Additional lives saved (1997-2011) Neonatal mortality rate, 1997 Neonatal mortality rate, 2011 % reduction in mortality (1997-2011) Additional lives saved (1997-2011) Maternal mortality ratio, 1997 Maternal mortality ratio, 2011 % reduction in mortality (1997-2011) Additional lives saved (1997-2011)
National 195.62 145.43 25.7% 422 282 50.36 41.31 18.0% 85 450 870.00 785.71 9.7% 6528
Niassa 200.05 134.01 33.0% 18 917 52.78 40.23 23.8% 6440 870.03 693.40 20.3% 558
Cabo Delgado 254.52 166.71 34.5% 58 807 54.48 50.45 7.4% 2911 965.93 933.33 3.4% 181
Nampula 237.18 145.22 38.8% 116 474 59.61 41.14 31.0% 28 746 909.95 739.41 18.7% 1798
Zambezia 241.89 196.79 18.6% 92 729 64.02 54.99 14.1% 22 236 977.15 914.34 6.4% 1153
Tete 204.36 160.02 21.7% 22 808 51.33 42.12 17.9% 2761 876.96 757.71 13.6% 288
Manica 199.71 138.15 30.8% 28 812 49.52 33.91 31.5% 8138 872.40 646.82 25.9% 891
Sofala 210.66 143.41 31.9% 37 057 50.16 35.69 28.8% 11 077 897.40 651.44 27.4% 1316
Inhambane 157.54 135.78 13.8% 9009 37.20 36.38 2.2% 82 751.57 699.17 7.0% 126
Gaza 161.42 128.65 20.3% 15 397 32.68 33.35 -2.1%* -248* 687.31 672.92 2.1% 1
Maputo Provincia 146.58 133.77 8.7% 5512 33.50 23.60 29.6% 2333 659.72 476.80 27.7% 228
Maputo Cidade 157.80 133.68 15.3% 16 760 30.31 30.50 -0.6%* 974* 597.12 618.53 -3.6%* -10

*A negative mortality reduction arises when intervention coverage decreases, resulting in fewer lives saved in 2011 than in 1997.



As mentioned in the introduction, we also have estimates of mortality from the DHS surveys in 1997, 2003, and 2011, which have been used by the UN Inter-agency Group for Child Mortality Estimation (UN IGME) to create an estimated trend of U5MR over time in Mozambique. This trend shows a more significant reduction in mortality over time than our modelled estimates, with a U5MR of 209 in 1997, 148 in 2003, and 95 in 2011 [10]. This stands to reason, since LiST only accounts for indicators that are inputted into the software. It is likely that other interventions, not inputted into our projections, also had an impact on mortality, resulting in a more significant reduction than suggested by our estimates.

Causes of death

Table 3 shows the proportion of deaths due to different causes in 1997 and 2011. In both years, malaria was the major cause of death among children under five, with approximately one in four deaths due to malaria. There was a decrease in the proportion of deaths due to measles, and an increase in the proportion of deaths caused by AIDS and wounds. Prematurity, asphyxia, and sepsis were the major causes of neonatal death in 1997 and 2011. From 1997 to 2011 the three major causes of maternal deaths were postpartum hemorrhage, other indirect causes of death, and antepartum hemorrhage. The major causes of death among children, neonates, and mothers at provincial level followed the same pattern as the causes of death at national level.

Table 3.  Top causes of death, in 1997 and 2011
Cause of death 1997 Cause of death 2011
Children (0-59 months):
Malaria 26% Malaria 22%
Diarrhea 12% Other 13%
Pneumonia 12% Pneumonia 10%
Other 10% Diarrhea 10%
Neonatal – Prematurity 7.8% Neonatal – Prematurity 9.0%
Neonatal – Asphyxia 7.5% Neonatal – Asphyxia 7.3%
Neonatal – Sepsis 4.5% AIDS 6.2%
Measles 4.2% Neonatal – Sepsis 4.4%
Meningitis 4.0% Wounds 4.2%
AIDS 3.0% Meningitis 4.1%
Wounds 3.0% Neonatal – Pneumonia 2.4%
Neonatal – Pneumonia 2.3% Measles 2.2%
Neonatal – Other 1.4% Neonatal – Other 1.9%
Neonatal – Congenital anomalies 1.3% Neonatal – Congenital anomalies 1.8%
Neonatal – Tetanus 1.0% Neonatal – Tetanus 0.7%
Whooping cough 0.7% Whooping cough 0.6%
Neonatal – Diarrhea 0.3% Neonatal – Diarrhea 0.3%
Total 100% Total 100%
Newborns (<1 months):
Neonatal – Prematurity 30% Neonatal – Prematurity 32%
Neonatal – Asphyxia 29% Neonatal – Asphyxia 26%
Neonatal – Sepsis 17% Neonatal – Sepsis 16%
Neonatal – Pneumonia 8.7% Neonatal – Pneumonia 8.7%
Neonatal – Other 5.3% Neonatal – Other 6.7%
Neonatal – Congenital anomalies 5.2% Neonatal – Congenital anomalies 6.5%
Neonatal – Tetanus 3.9% Neonatal – Tetanus 2.5%
Neonatal – Diarrhea 1.0% Neonatal – Diarrhea 1.1%
Total 100% Total 100%
Mothers:
Postpartum hemorrhage 24% Other indirect 26%
Other indirect 22% Postpartum hemorrhage 20%
Antepartum hemorrhage 13% Antepartum hemorrhage 12%
Sepsis 11% Sepsis 11%
Hypertensive diseases of pregnancy 11% Hypertensive diseases of pregnancy 9.0%
Other direct 6.9% Other direct 8.3%
Hypertensive diseases of pregnancy 4.9% Abortion 6.1%
Abortion 4.7% Obstructed labor 4.4%
Ectopic 1.1% Malaria 1.6%
Malaria 1.0% Ectopic 1.3%
Total 100% Total 100%


Additional lives saved

Our modelled estimates show that increases in intervention coverage from 1997 to 2011 saved an additional 422 282 child lives (0-59 months), 85 450 neonatal lives (0-1 month), and 6528 maternal lives beyond those already being saved at baseline. We calculated the number of additional lives saved for each intervention. We did this separately for the periods 1997-2011 and 2011-2015 because, as described above, we had limited data for the year 2015, and we did not want to under-represent the impact of certain interventions in the 2011-2015 period because of this lack of data. The full list of interventions and their additional lives saved is provided in Appendices S3-S5 in Online Supplementary Document(Online Supplementary Document). Tables 4 and 5Table 5 present the 10 interventions for each age category that were responsible for the most additional lives saved, resulting from the increase in coverage of these interventions beyond the baseline year (1997 for Table 4 and 2011 for Table 5).

Table 4.  Top 10 interventions for additional lives saved (1997-2015)
Intervention National
Children (0-59 months):
Additional lives saved (1997-2011) % of lives saved (1997-2011) Additional lives saved (2011-2015) % of lives saved (2011-2015)
Change in wasting prevalence 82 374 20% Data not available for 2015
ITN/IRS 55 757 13% Data not available for 2015
Artemisinin compounds (ACTs) for treatment of malaria 34 807 8% 11 920 41%
Oral antibiotics for pneumonia 29 804 7% 1149 4%
Changes in breastfeeding 27 405 6% Data not available for 2015
Measles vaccine 26 432 6% 229 1%
Labor and delivery management 24 041 6% 3243 11%
Change in stunting prevalence 19 257 5% Data not available for 2015
Preventing mother to child transmission (PMTCT) 19 101 5% 3621 13%
Full supportive care, sepsis/pneumonia 15 928 4% Data not available for 2015
Other 87 376 21% 8580 30%
Total 422282 100% 28742 100%
Newborns (<1 months):
Labor and delivery management 24 041 28% 3243 29%
Changes in breastfeeding 16 526 19% Data not available for 2015
Full supportive care for neonatal sepsis/pneumonia 15 928 19% Data not available for 2015
Tetanus toxoid vaccination 7867 9% Data not available for 2015
Neonatal resuscitation 6335 7% 1590 14%
Clean birth practices 3290 4% 941 8%
Thermal care 3129 4% 767 7%
Immediate assessment and stimulation 2909 3% 950 8%
Antibiotics for pPRoM 2152 3% 227 2%
Oral antibiotics for neonatal sepsis/pneumonia 1691 2% Data not available for 2015
Other 1582 2% 3572 32%
Total 85450 100% 11290 100%
Mothers:
Labor and delivery management 3118 48% 275 31%
Active management of the third stage of labor (AMTSL) 1163 18% 135 15%
MgSO4 management of eclampsia 801 12% 93 11%
Clean birth practices 740 11% 243 27%
Antibiotics for pPRoM 462 7% 56 6%
Tetanus toxoid vaccination 97 1% Data not available for 2015
Contraceptive use 82 1% Data not available for 2015
MgSO4 management of pre-eclampsia 23 0% 2 0%
Hypertensive disorder case management 21 0% 3 0%
Malaria case management 11 0% 0 0%
Other 10 0% 77 9%
Total 6528 100% 884 100%

ITN/IRS – Insecticide-treated nets/indoor residual spraying, ACTs – artemisinin compounds, pPRoM – preterm premature rupture of the membranes, AMTSL – active management of the third stage of labor, MGSO4 – magnesium sulfate



Table 5.  Top 10 interventions for additional lives saved (2011-2015)
Intervention National
Additional lives saved (2011-2015) % of lives saved
Children (0-59 months):
Artemisinin compounds (ACTs) for treatment of malaria 11 920 41%
PMTCT 3621 13%
Labor and delivery management 3243 11%
Injectable antibiotics for neonatal sepsis/pneumonia 2977 10%
Neonatal resuscitation 1590 6%
Oral antibiotics for pneumonia 1149 4%
Immediate assessment and stimulation 950 3%
Clean birth practices 941 3%
Thermal care 767 3%
Intermittent preventive treatment of malaria during pregnancy (IPTp) 525 2%
Other 1059 4%
Total 28742 100%
Newborns (<1 months):
Labor and delivery management 3243 29%
Injectable antibiotics for neonatal sepsis/pneumonia 2977 26%
Neonatal resuscitation 1590 14%
Immediate assessment and stimulation 950 8%
Clean birth practices 941 8%
Thermal care 767 7%
Intermittent preventive treatment of malaria during pregnancy (IPTp) 525 5%
Antibiotics for pPRoM 227 2%
Syphilis detection and treatment 56 0%
Preventing mother to child transmission (PMTCT) 14 0%
Other 0 0%
Total 11 290 100%
Mothers:
Labor and delivery management 275 31%
Clean birth practices 243 27%
Active management of the third stage of labor (AMTSL) 135 15%
MgSO4 management of eclampsia 93 11%
Intermittent preventive treatment of malaria during pregnancy (IPTp) 77 9%
Antibiotics for pPRoM 56 6%
Hypertensive disorder case management 3 0%
MgSO4 management of pre-eclampsia 2 0%
Other 0 0%
Total 884 100%

pPRoM – preterm premature rupture of the membranes, MGSO4 – magnesium sulfate



For children under five between 1997 and 2011, the most additional lives saved were contributed by interventions to reduce the prevalence of wasting (82 374 or 20% of all additional lives saved), increased coverage of insecticide-treated bed nets/indoor residual spraying (55 757 or 13%), and increased coverage of ACTs for malaria (34 807 or 8%). Although we have no data for changes in wasting prevalence and ITN/IRS coverage from 2011 to 2015, increased ACT coverage contributed a high percentage (41%) of additional lives saved from 2011 to 2015, with increased coverage of prevention of mother-to-child transmission (PMTCT) contributing the second highest percentage (13%).

From 1997 to 2011, and from 2011 to 2015, increased coverage of neonatal interventions contributed 85 450 and 11 290 additional neonatal lives saved, respectively. Increased coverage of labor and delivery management (28%), breastfeeding promotion (19%), and full supportive care for neonatal sepsis/pneumonia (19%) contributed the largest proportion of additional lives saved from 1997 to 2011. From 2011 to 2015, labor and delivery management continued to add the largest proportion of lives saved (29%), with no data available for breastfeeding promotion and full supportive care for neonatal sepsis/pneumonia. Among the 6528 and 884 additional maternal lives saved for 1997-2011 and 2011-2015 respectively, the increased coverage of labor and delivery management contributed about half (58%) and one third (31%) of additional lives saved, respectively, followed by increased coverage of active management of the third stage of labor (AMTSL), magnesium-sulfate (MgSO4) for the management of eclampsia, and clean birth practices.

We have not presented our results of additional lives saved by intervention at provincial level, but these are available in Appendices S3-S5 in Online Supplementary Document(Online Supplementary Document).

DISCUSSION

Since 1997, Mozambique has seen a considerable reduction in child mortality, reflecting the efforts made by the Ministry of Health to scale up proven child health interventions and roll out new interventions. Various vaccines were introduced over the past eight years (Pentavalent3/DPT3, pneumococcal and rotavirus); a national ITN household ownership strategy was rolled out in 2011; the implementation of pediatric ART and PMTCT was introduced in 2002 in Maputo and later in the remainder of the country; and a breastfeeding promotion strategy was begun in 2009 [14]. These efforts should be recognized and celebrated for their contributions to improving child health.

Our findings also offer details about the changes in coverage over 15 years (1997-2011) that contributed the most additional lives saved among children under five – in other words, the efforts that had the biggest impact. We found that wasting and malaria interventions were responsible for most of the additional mortality reduction. However, we also found that malaria and malnutrition are still responsible for significant mortality in Mozambique, and thus continue to represent an opportunity to decrease child mortality further. In our analysis, more than one quarter of children were stunted in 2011, and malaria remains the biggest killer of children under five. A 2007 cause-of-death survey in Mozambique corroborates these findings, suggesting that malaria was responsible for 42.3% of under-five deaths [15]. These data highlight the importance and timeliness of recent further increases in government health financing to reduce under-five mortality [16].

Although increased coverage of interventions did reduce neonatal and maternal mortality in most provinces, the increase was not consistent and was limited in some areas, especially in Cabo Delgado, Gaza, and Maputo City. We found that interventions related to labor and delivery management averted more than half of the maternal deaths and more than one quarter of the neonatal deaths in the last 19 years. However, interventions related to prevention of maternal mortality such as antenatal care, skilled birth attendance, and institutional delivery showed lower coverage increases compared to other preventive and curative interventions, hence the smaller reduction in maternal mortality from 1997 to 2011 compared to child mortality. While there was an increase in coverage of facility delivery to more than 90% in Maputo Province in 2011, other provinces have yet to achieve such coverage of facility delivery or antenatal care. Additionally, only one fifth of pregnant women received preventive treatment for malaria in 2011 at national level. This may be due to a limited awareness of the consequences of malaria in pregnancy, especially for newborns [17].

The findings from this paper emphasize the success of the government in increasing coverage of existing interventions saving hundreds of thousands of additional lives, beyond those that were already being saved by existing coverage of interventions in 1997. This highlights the value of a multi-targeted approach, increasing awareness and uptake of new strategies, while further increasing access to and utilization of existing interventions. However, with all this in mind, more must be done not only to improve the coverage of interventions but also to improve the quality of such interventions, requiring more attention to policy implementation and health service delivery. Policy-makers should also ensure that gaps in intervention coverage are reduced not only in wealthy or urban areas of the country, but equitably across Mozambique. A multi-country analysis for low and middle income countries showed that both relative and absolute wealth-related and educational inequalities in maternal and neonatal health decreased in the last decade in Mozambique [18]. Nevertheless, in countries with low levels of antenatal care such as Mozambique, scaling up this service to rural and underserved areas might be an effective strategy to reduce health inequities.

Limitations

As a retrospective analysis of secondary data, we depended on the data available to us. We were only able to include indicators modelled in LiST and indicators for which we had reliable data. Specifically, due to the limited number of interventions in the 2015 IMASIDA survey data set, we could not reliably estimate trends in mortality or causes of death for 2011-2015, or compare additional lives saved in that period with the 1997-2011 period. As such, we were only able to report most results for 1997-2011. Data limitations during the 1997-2011 period also explain why the mortality trends generated by our LiST projections (Table 2) under-represent the decline in mortality reported in DHS surveys from 1997, 2003, and 2011. The mortality decline in our projections only captures the coverage changes for interventions that we could model.

While these limitations raise questions about our mortality rate calculations, they do not negate the value of our intervention-specific findings on additional lives saved. Even for the 2011-2015 period, our findings reflect accurately the additional lives saved attributable to those interventions for which we have data – the lack of data on other interventions does not affect our estimates for the interventions for which we do have data. Although LiST does not allow users to produce confidence intervals for uncertain coverage estimates, this paper nonetheless offers important estimates for the relative impact of interventions, an output that can help to define priority interventions in the future. This analysis also highlights the value of using existing survey data to understand the health landscape in Mozambique, especially as routine health information system (HIS) data on mortality and causes of death are still lacking at both national and provincial levels.

CONCLUSION

The findings from our analysis and previous surveys of mortality show that Mozambique has made great strides towards achieving MDG 4. Efforts to achieve MDG 5 have been less fruitful. Mozambique should continue striving to reduce child, neonatal, and maternal mortality – to achieve the SDGs by 2030, but more importantly to improve the lives of women and children across the country. Further commitments to interventions that we know save lives, such as ITN/IRS and improved labor and delivery management, should be sought, and additional effort should be made to monitor the impact of interventions on child and maternal health. More lives can be saved by continuing to increase coverage of existing health interventions and exploring new ways to reach underserved populations.

Acknowledgements

We would like to acknowledge and thank the following members of the Technical Working Group of the National Evaluation Platform Approach for Accountability in Women’s and Children’s Health (NEP-Mozambique): José Braz Chidassicua, José Maiane Junior, Jose Cardoso, Júlia Sambo, María Patrícia Gonçalves, Marla Amaro, Samuel Fenias, and Réka Maulide Cane.

Notes

[1] Funding: The authors wish to acknowledge the Department of Global Affairs Canada for their support of the NEP.

[2] Authorship declaration: MC and KN gathered secondary data for the analysis. All authors participated in data analysis using the Lives Saved Tool. IM, AM and TR prepared the first version of the manuscript. All authors provided comments on subsequent drafts and approved the final version of the manuscript.

[3] Competing interests: All authors have completed a Unified Competing Interest form at www.icmje.org/coi_disclosure.pdf and declare no conflict of interest.

REFERENCES

[1] United Nations Foundation. What We Do: The Millennium Development Goals [Internet]. 2012. Available: http://www.unfoundation.org/what-we-do/issues/mdgs.html. Accessed 08 May 2017.

[2] Instituto Nacional de Estatistica. Moçambique Inquérito Demográfico e de Saúde 1997 [Internet]. 1998 Sept. Available: http://www.ine.gov.mz/operacoes-estatisticas/inqueritos/inquerito-demografico-e-de-saude/ids-1997.pdf/view. Accessed 08 May 2017.

[3] Instituto Nacional de Estatistica. Moçambique Inquerito Demografico e de Saúde 2003 [Internet]. 2005 Jun. Available: http://www.ine.gov.mz/operacoes-estatisticas/inqueritos/inquerito-demografico-e-de-saude/ids-2003.pdf/view. Accessed 08 May 2017.

[4] Instituto Nacional de Estatistica. Moçambique - Inquerito Demografico e de Saúde, Demographic Health Surveys (DHS) - Visăo global [Internet]. 2011. Available: http://mozdata.microdatahub.com/index.php/catalog/15/study-description. Accessed 08 May 2017.

[5] República de Moçambique Ministério da Saúde. Plano Estratégico do Sector da Sade 2014-2019. Maputo; 2013.

[6] N Walker, Y Tam, and IK Friberg. Overview of the Lives Saved Tool (LiST). BMC Public Health.2013;13:Suppl 3S1 DOI: 10.1186/1471-2458-13-S3-S1. [24564438]

[7] AR Stegmuller, A Self, K Litvin, and T Roberton. How is the Lives Saved Tool (LiST) used in the global health community? Results of a mixed-methods LiST user study. BMC Public Health.2017;17:773 DOI: 10.1186/s12889-017-4750-5. [29143640]

[8] W Winfrey, R McKinnon, and J Stover. Methods used in the Lives Saved Tool (LiST). BMC Public Health.2011;11:S32 DOI: 10.1186/1471-2458-11-S3-S32. [21501451]

[9] A Amouzou, M Kanyuka, E Hazel, R Heidkamp, A Marsh, and T Mleme. Independent Evaluation of the integrated Community Case Management of Childhood Illness Strategy in Malawi Using a National Evaluation Platform Design. Am J Trop Med Hyg.2016;94:574-83. DOI: 10.4269/ajtmh.15-0584. [26787158]

[10] United Nations Inter-agency Group for Child Mortality Estimation (UN IGME). Levels & Trends in Child Mortality: Report 2017, Estimates Developed by the UN Inter-agency Group for Child Mortality Estimation. 2017. United Nations Children’s Fund, New York. 2017.

[11] Trends in maternal mortality: 1990 to 2015. Estimates by WHO, UNICEF, UNFPA, World Bank Group and the United Nations Population Division. 2015. Available from: http://www.who.int/reproductivehealth/publications/monitoring/maternal-mortality-2015/en/. Accessed 08 May 2018.

[12] L Liu, S Oza, D Hogan, Y Chu, J Perin, and J Zhu. Global, regional, and national causes of under-5 mortality in 2000–15: an updated systematic analysis with implications for the Sustainable Development Goals. Lancet.2016;388:3027-35. DOI: 10.1016/S0140-6736(16)31593-8. [27839855]

[13] L Say, D Chou, A Gemmill, Ö Tunçalp, AB Moller, and J Daniels. Global causes of maternal death: a WHO systematic analysis. Lancet Glob Health.2014;2:e323-33. DOI: 10.1016/S2214-109X(14)70227-X. [25103301]

[14] República de Moçambique. Aprofundamento para o Relatório de Avaliaçăo do Impacto PARPA II (2006-2009): Área de Nutriçăo. 2009.

[15] Instituto Nacional de Estatística. Inquérito Nacional sobre Causas de Mortalidade 2007/8 [Internet]. 2009. Available: http://www.ine.gov.mz/operacoes-estatisticas/inqueritos/inquerito-sobre-causas-de-mortalidade/inquerito-nacional-sobre-causas-de-mortalidade-2007-8.pdf/view. Accessed 08 May 2018.

[16] QF Fernandes, BH Wagenaar, L Anselmi, J Pfeiffer, S Gloyd, and K Sherr. Effects of health-system strengthening on under-5, infant, and neonatal mortality: 11-year provincial-level time-series analyses in Mozambique. Lancet Glob Health.2014;2:e468-77. DOI: 10.1016/S2214-109X(14)70276-1. [25103520]

[17] CC Diala, T Pennas, C Marin, and KA Belay. Perceptions of intermittent preventive treatment of malaria in pregnancy (IPTp) and barriers to adherence in Nasarawa and Cross River States in Nigeria. Malar J.2013;12:342 DOI: 10.1186/1475-2875-12-342. [24059757]

[18] B McKinnon, S Harper, JS Kaufman, and Y Yves Bergevin. Socioeconomic inequality in neonatal mortality in countries of low and middle income: a multicountry analysis. Lancet Glob Health.2014;2:e165-73. DOI: 10.1016/S2214-109X(14)70008-7. [25102849]

Additional Material


Journal of Global Health (ISSN 2047-2986), Edinburgh University Global Health Society
Designed by