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. 2025 May 23;20(5):e0324122. doi: 10.1371/journal.pone.0324122

Mortality rates in a cohort of infants attending immunization clinics in Uganda (2017–2019)

Samuel Sendagala 1,*, Rose Bosa Nakityo 1, Fredrick Makumbi 2, Tom Lutalo 2, Linda Nabitaka 3, Fred Nalugoda 2, Ivan Lukabwe 3, Jingo Kasule 2, Emily Namara-Lugolobi 1, Margaret Achom Okwero 1, Hilda T Asiimwe 4, Phoebe Namukanja 1, Bernadette Ng'eno 5, Emilio Dirlikov 1, Augustina Delaney 5
Editor: Emma K Kalk6
PMCID: PMC12101647  PMID: 40408421

Abstract

Background

Uganda reported a significant reduction in the mortality rate of children under 5 years of age, from 146/1,000 live births in 2000–42/1,000 live births in 2021. With the rollout of Option B+, the vertical transmission rate of HIV decreased from 13.0% (2012) to 6.0% (2019). However, its impact on the mortality rate among children is not well documented. We determined the mortality rate and associated risk factors among infants exposed and not exposed to HIV attending immunization clinics in Uganda.

Methods

We conducted an observational prospective cohort study of mother–infant pairs (MIPs) with infants exposed or unexposed to HIV. We enrolled infants aged 4–12 weeks. The inclusion criteria were biological mothers attending health facilities that provide routine immunization for children and/or postnatal care visits who were able to provide signed written informed consent; mothers or infants who were not severely ill; and those who consented to have their infants tested for HIV antibodies at baseline and follow-up visits every 3 months until the children were aged 18 months. Child-HIV infection and death were censored events. Children lost to follow-up or withdrawn from the study were censored from analyses at the last documented study visit. The outcome of interest was child mortality, and the independent variables were mother’s age; infant HIV exposure status; infant sex; family socioeconomic status; marital status; education level; malaria during pregnancy; birth attendee; mother’s ART initiation; mode of transport to health facilities; breastfeeding pattern; 4 or more ANC visits; and mother’s baseline viral load nonsuppression and place of delivery. We used Kaplan–Meier survival curves to estimate cumulative mortality probability and the Wilcoxon log-rank test to compare differences in cumulative survival functions. We used multivariate Weibull proportional hazards and Weibull accelerated failure time (AFT) regression models with 95% confidence intervals (CIs) to identify factors associated with child death.

Results

Among the 16,718 MIPs identified, 11,519 (68.9%) mothers consented to study follow-up. At the 18-month follow-up, 0.7% (79/11,519) of the infants had died, 40.5% (32/79) of whom were exposed to HIV. The overall child mortality rate per 1,000 person-years was 5.0 (95% CI: 4.0--6.2) and was significantly greater among the infants exposed to HIV (14.2; 95% CI: 10.0--20.0) than among the infants not exposed to HIV (3.5; 95% CI: 2.6--4.6). In the adjusted model, the mortality risk factors were HIV exposure status (aHR5.6 95% CI: 3.5--9.4), maternal age < 25 years (aHR1.8; 95% CI: 1.1--2.9), living without a partner (aHR1.8; 95% CI: 1.1--2.9), and delivery at home (aHR2.2; 95% CI: 1.3--4.0).

Conclusion

Single young mothers living with HIV delivering at home increased the risk of child mortality. Identifying mothers with risk factors early for support could reduce the risk of child mortality.

Introduction

In 2021, 5.0 million children died before they reached the age of 5 years, and 56% (2.8 million) were in sub–Saharan Africa, despite the region accounting for 29% of the global live births [1]. There has been a 59% reduction in the child underfive mortality rate (U5MR) globally in previous decades, from 93 to 38 deaths per 1,000 live births between 1990 and 2021. However, the reduction in the U5MR in sub-Saharan Africa (SSA) was slower than that in other regions, with 74 deaths per 1,000 live births in 2021 [1]. The implementation of the United Nations’ Sustainable Development Goals (SDGs) started in 2016 with a target U5MR of no more than 25 deaths per 1,000 live births in every country of the world by 2030 [2]. Uganda has yet to achieve this target, with a current U5MR of 42 deaths per 1,000 live births in 2021 [1].

Globally, communicable and infectious diseases such as pneumonia, diarrhea, HIV/AIDS, and malaria continue to be the leading causes of preventable underfive deaths [3]. Other factors, such as death of the mother, child vaccination status, breastfeeding status and low birth weight, have also been shown in several studies to be associated with morbidity and mortality among infants and are more pronounced among infants exposed than those not exposed to HIV [46]. Mosley et al.’s analytical approach to the study of the determinants of child survival in low- and middle-income countries highlights the premise that all socioeconomic determinants, such as income/wealth, the political economy and the health system of child mortality, operate through a common set of biological mechanisms or proximate determinants, such as maternal factors, nutrition, and personal illness control, to affect mortality [7].

Exposure to HIV has been widely documented to be a risk factor for infant mortality in the ZVITAMBO trial, which reported a 2-year mortality rate of 9.2% in infants exposed but not infected compared with 2.9% in those not exposed to HIV [8,9]. However, maternal antiretroviral therapy (ART) use during pregnancy and breastfeeding has been shown to reduce mortality in children under 5 years of age to levels observed in children of mothers not infected with HIV in South Africa [10]. Young mother, illiteracy and income inequality have been documented to predict the infant mortality rate (IMR) in low- and middle-income countries [11]. In 2013, in accordance with the WHO guidelines, Uganda was among the first countries in sub-Saharan Africa to incorporate Option B+ (life-long universal maternal antiretroviral therapy (ART)) into its national prevention of vertical transmission of HIV strategy [12]; since then, the percentage of pregnant and breastfeeding women living with HIV receiving lifelong ART has increased from <1% to >95%, and transmission rates have decreased from 24% to 6% from 2010–2019 [1217]. Uganda is a country with a mature generalized HIV epidemic, with an HIV prevalence of 5.8% among adults aged 15 years plus approximately 1.5 million people living with HIV [18]. Over time, the HIV epidemic has had a negative impact on overall child mortality rates in the country; thus, with increased access to ART for pregnant women living with HIV, the rate of HIV-related child mortality has been declining in Uganda. To determine child mortality rates and associated risk factors among infants exposed and not exposed to HIV, we analyzed data from the evaluation of the Impact of the national program for prevention of vertical transmission of HIV in Uganda, a nationally representative cohort of infants exposed and not exposed to HIV in Uganda up to 18 months postdelivery.

Methods

We analyzed data collected as part of the Uganda prevention of vertical transmission of HIV impact evaluation study, a prospective observational cohort study of vertical transmission of HIV. The study included a nationally representative sample of mother–infant pairs (MIPs), including infants exposed and those not exposed to HIV, recruited from immunization clinics within health facilities from 20th September 2017–26th February 2018. The health facility sampling frame included all private and public facilities that offered infant first DPT vaccination in 2015, of which 206 health facilities were randomly selected without replacement. Infants aged 4–12 weeks and their biological mothers receiving routine health care at the selected facilities were screened. Trained research assistants obtained written consent and enrolled mother–infant pairs. Mother-infant pairs were excluded if the infant or mother was severely ill or if the mother did not consent to infant HIV testing. The infants were followed until incident HIV infection, death, or 18 months of age. MIPs had follow-up visits at 6, 9, 12, 15, and 18 months postpartum, with a ±6-week allowance for follow-up visits. All infants exposed to HIV were assessed for HIV infection at follow-up visits with infants aged <18 months via HIV DNA PCR via dried blood spots and those aged ≥18 months through onsite rapid antibody testing. For mothers living without HIV, at every visit, they were screened for new HIV infection via onsite rapid antibody testing. In addition, mothers living with HIV underwent maternal viral load testing at the 6- and 12-month follow-up visits. Data were obtained through maternal and infant questionnaires and abstraction of selected clinical variables from the child’s Child Health Card (CHC).

Child characteristics collected at baseline included age, sex, birth weight (low, defined as < 2.5 kg), feeding practices from birth to enrollment (exclusive breastfeeding or not), and HIV exposure status. Maternal characteristics collected at baseline included age, marital status, education, HIV viral load suppression (<1000 copies/ml), type of birth attendee, malaria during pregnancy, gestational age at antenatal care (ANC) enrollment, place of infant delivery, mode of transport to nearest health facility, and maternal ART status (the timing of maternal ART initiation). Socioeconomic status (SES) index by quintiles was a composite measure derived from household income and assets.

Child mortality was defined as any child death that was verbally reported by the mother or caretaker (not a biological mother) during the follow-up period. We defined a child as an infant exposed to HIV, if it was born to a mother who had an HIV-positive status confirmed by data from either the CHC, ANC card, maternal outpatient card, or rapid HIV test result during any study visit. Children were defined as an infant not exposed, if they were born to a mother who had an HIV-negative status and did not seroconvert during the study.

Statistical analysis

Our outcome of interest was all-cause child mortality within the follow-up period to child age 18 months. Children who experienced the primary endpoint of the parent study (HIV infection via vertical transmission of HIV) at the baseline visit were excluded from analysis. Children who were lost to follow-up (i.e., unable to contact or locate participants for three consecutive missed appointment visits) or withdrew from the study for other reasons (i.e., refusal to continue or relocate out of the study area) and children who seroconverted during the follow-up period were censored from mortality analyses on the date recorded on the study suspension form or the last recorded study visit; their time at risk was age at their last visit. The time at risk for children who died was age at death. We calculated percentages, median values, and mortality rates per 1,000 person-years for maternal and child characteristics. We estimated the cumulative mortality probability via Kaplan–Meier curves and the log-rank test to compare differences in cumulative survival functions among infants exposed and those not exposed to HIV. We used plots of the log-log of survival functions to assess for Cox proportional hazards assumptions that were violated for most of the independent variables. For multivariate analysis, we therefore used Weibull proportional hazards and Weibull accelerated failure time (AFT) regression models with 95% confidence intervals (CIs) to identify factors associated with hazard of child death. To identify independent factors associated with child death, stepwise regression with the minimum Akaike information criterion (AIC) between the full model and the reduced model was used to identify variables to include in the final model. The strength of the association was expressed as adjusted hazard ratios and associated 95% CIs as well as failure time ratios with a 5% level of statistical significance. We used multiple imputation by chained equation (MICE) to impute missing values for variables with less than 10% missing values to avoid bias when more than 10% of the data were missing [19]. Variables with more than 10% missing data were dropped from the model. The imputed variables were infant sex, feeding practice, maternal age, marital status, socioeconomic status, malaria during pregnancy, mode of transport to health facilities, place of delivery and number of ANC visits. We conducted 20 imputations to create a set of conditional distributions for each imputed variable, which replaced the missing value with a set of plausible values that represent the uncertainty about the value to impute.

The analyses were not weighted for the complex survey design of the parent study. All the statistical analyses were conducted in Stata 16.0 (StataCorp, Lakeway Drive, Texas, USA).

Ethical considerations

This study was reviewed and approved by the Uganda Virus Research Institute (UVRI) IRB with reference number GC/127/17/03/579 and registered with the Uganda National Council for Science and Technology (See 45 C.F.R. part 46.114; 21 C.F.R. part 56.114). All the participating mothers or caregivers provided written consent at the baseline and follow-up enrollment visits.

Results

A total of 11,519 (68.9%) of the 16,718 infants identified were enrolled in the study, with a median age of 56 days (IQR 46–64); 50.0% were male, and 87.1% were exclusively breastfed in the first 6 months. More than half of the mothers (63.4%) were aged 15–24 years. A total of 1,723 (15.0%) children were HIV-exposed by the end of the study; of these, 63.1% of the mothers were on ART before conception, and 88.2% of the mothers with a baseline HIV viral load had a suppressed viral load. In total, 79 (0.7%) children died, 32/79 (40.5%) of whom were infants exposed to HIV (Table 1).

Table 1. Baseline characteristics of mother–infant pairs by child mortality status (N = 11,519).

Characteristics Dead, N = 79 n (%) Alive, N = 11440 n (%) All, N = 11519 n (%) P value
Infants
Age at baseline (days), median (IQR) 56 (45–65) 56 (46–64) 56 (46–64)
Sex
  Male 37 (43.0) 5698 (49.9) 5735 (50.0)
  Female 42 (57.0) 5687 (50.1) 5729 (50.0) 0.5695
Birth weight
  Low (<2.5 kgs) 1 (2.1) 540 (7.2) 541 (7.2)
  Not Low (>=2.5 kgs) 46 (97.9) 6949 (92.8) 6995 (92.8) 0.1784
Feeding practice (first 6 months)
  Exclusively breastfed first 6 months 67 (85.2) 9926 (87.1) 9993 (87.1)
  Mixed/replacement feeding first 6 months 9 (14.8) 1378 (12.9) 1387 (12.9) 0.7035
HIV Exposure Status
  Unexposed 47 (59.5) 9750 (85.2) 9797 (85.0)
  Exposed 32 (40.5) 1691 (14.8) 1723 (15.0) <.0001
Maternal
Age
  15-24 years 52 (69.1) 7263 (63.4) 7315 (63.4)
  25 years and older 27 (30.9) 4125 (36.6) 4152 (36.6) 0.7063
Marital Status
  Living without a Partner 26(33.8) 2289(20.6) 2315 (20.7)
  Living with a Partner 51 (66.2) 8829(79.4) 8880(79.3) 0.4220
Education
  Above primary 42 (33.5) 3532 (32.1) 3557 (32.1)
  Primary and below 54 (66.5) 7908 (67.9) 7962 (67.9) 0.8816
Social Economic Status
  High (4th or 5th quintile) 22 (27.4) 4093 (36.3) 4115 (36.3)
  Low (1st or 2nd quintile) 38 (53.1) 4914 (43.6) 4952 (43.6) 0.1762
  Middle (3rd quintile) 17 (19.5) 2268 (20.1) 2285 (20.1) 0.3051
Birth attendee
  Skilled 38 (77.8) 6904 (85.6) 6942 (85.6)
  Traditional birth attendants(TBA)/Others 11 (22.2) 1179 (14.4) 1190 (14.4) 0.1248
Malaria in Preganacy
  Yes 59 (77.4) 8478 (74.4) 8537 (74.4) 0.8309
  No 19 (22.6) 2889 (25.6) 2908 (25.6)
Gestation Age at start of ANC
  0-3 months 22 (31.4) 3099 (30.4) 3121 (30.4)
  4-6 months 43 (61.4) 6334 (62.1) 6377 (62.1) 0.8651
  7-9 months 5 (7.2) 765 (7.5) 770 (7.5) 0.8680
Mode of transport to health facility
  Walking 51 (71.2) 6631 (58.4) 6682 (58.1) 0.2421
  Motorized 28 (28.8) 4798 (41.6) 4826 (41.9)
ART Status (HIV infected only)*
  Initiated preconception 14 (51.9) 924 (63.0) 938 (62.8)
  Initated during pregnancy/Identified during pregnancy 10 (37.0) 417 (28.4) 427 (28.6) 0.2723
  Initiated post delivery/Identified Positive during study 3 (11.1) 117 (8.0) 120 (8.0) 0.4138
  Don’t know 0 (0) 8 (0.6) 8 (0.6) 0.9911
Suppressed HIV Virally Load (<1000 copies/ml) at baseline(mothers living with HIV only)
  Suppressed 26 (81.7) 1283 (88.3) 1309 (88.2)
  Not suppressed 4 (18.3) 165 (11.7) 169 (11.8) 0.7415
Place of delivery
  Public Facility 40 (53.7) 6905(61.4) 6945 (61.3)
  Home 17 (20.1) 1542(13.7) 1559 (13.8) 0.0270
  Private Facility 20 (26.2) 2797(24.9) 2817 (24.9) 0.4437

aMissing: Infant Sex: n = 55(0.5%); Birth weight: n = 4450 (38.6%);Feeding practice: n = 139(1.2%); Maternal age: n = 52(0.5%); Marital status: n = 320 (2.8%); Social Economic Status: n = 167 (1.5%); Viral load suppression: n = 244(2.1%); Birth attendee: n = 3387 (29.4)%; Malaria in Pregnancy: n = 74 (0.6%); Gestation Age at start of ANC: n = 1251 (10.9%); Mode of transport to health facility: n = 11 (0.1%); ART status: n = 229 (2.0%); Place of delivery: n = 194 (1.7%).

*The timing of maternal ART initiation for mothers living with HIV.

The overall child mortality rate was 5.0 per 1,000 person-years (95% CI: 4.0–6.2). HIV-exposed children and those born at home had significantly greater risks of death (p ≤ 0.0000 and p = 0.03, respectively). Mortality rates were significantly higher for infants exposed (14.2, 95% CI: 10.0–20.0) compared to those not exposed to HIV (3.5, 95% CI: 2.6–4.6); mothers not living with their partners (8.5, 95% CI: 5.8–12.4) compared to those living with a partner (4.1, 95% CI: 3.1–5.4) and infants born at home compared (7.8, 95% CI: 4.8–12.6) to those born at a public facility (4.2, 95% CI: 3.1–5.7) (Table 2).

Table 2. Child mortality rate per 1,000 person-years during the 18-month follow-up period.

Characteristic Deaths Number of Infants Person years of infant age MR per 1000 person years 95%CI p values
Infants
 Overall 79 11519 15870.5 5 [4.0–6.2]
Sex
  Male 37 5735 7894.6 4.7 [3.4–6.5]
  Female 42 5730 7905.4 5.3 [3.9–7.2] 0.5781
Feeding practice (first 6 months)
  Mixed/replacement feeding first 6 months 9 1387 1921.7 4.7 [2.4–9.0]
  Exclusively breastfed first 6 months 67 9993 13760.2 4.9 [3.8–6.1] 0.7110
HIV exposure status
  Unexposed 47 9797 13613.2 3.5 [2.6–4.6]
 Exposed 32 1723 2257.3 14.2 [10.0–20.0] <.0001
Maternal
Age
  15-24 years 52 7316 10068.2 5.2 [3.9–6.8]
  25 years and older 27 4152 5732.1 4.7 [3.2–6.9] 0.6978
Marital Status
  Living without a partner 26 2315 3068.4 8.5 [5.8–12.4]
  Living with a partner 51 8880 12380.2 4.1 [3.1–5.4] 0.0028
Education
  Above Primary Level 25 3552 4919.3 5.1 [3.4–7.5]
  None/Primary/Don’t Know 54 7741 10951.3 4.9 [3.8–6.4] 0.9007
Social Economic Status
  High (4th or 5th quintile) 22 4115 5646.7 3.9 [2.6–5.9]
  Low (1st or 2nd quintile) 38 4952 6832.5 5.6 [4.0–7.6] 0.1840
  Middle (3rd quintile) 17 2285 3162.7 5.4 [3.3–8.6] 0.3190
Birth attendee
  Skilled 38 6942 9526.0 4.0 [2.9–5.5]
  Traditional birth attendant (TBA)/Other 11 1190 1645.3 6.7 [3.7–12.1] 0.1315
Malaria in preganacy
  No 59 8537 11769.9 5.0 [3.9–6.5]
  Yes 19 2908 4001.6 4.7 [3.0–7.4] 0.8370
Gestation Age at start of ANC
  0-3 months 22 3121 4263.8 5.2 [3.4–7.8]
  4-6 months 43 6377 8813.7 4.9 [3.6–6.6] 0.8309
  7-9 months 5 770 1058.7 4.7 [1.9–11.3] 0.8582
Mode of transport to Health Facility
  Motorize 28 4826 6640.7 4.2 [2.9–6.1]
  Walking 51 6682 9214.5 5.5 [4.2–7.3] 0.2474
ART Status (HIV infected only)
  Initiated preconception 14 938 1256.2 11.1 [6.6–18.8]
  Initated during pregnancy/Identified during pregnancy 10 427 549.8 18.2 [9.7–33.8] 0.2368
  Initiated post delivery/Identified Positive during study 3 120 143.1 21 [6.7–65.0] 0.3205
Suppressed HIV Viral Load (<1000 copies/ml) at baseline(mothers living with HIV only)
  Suppressed 26 1310 1737.4 15.0 [10.2–22.0]
  Not suppressed 4 169 214.2 18.7 [7.0–49.8] 0.6808
Place of delivery
  Public Facility 40 6945 9557.3 4.2 [3.1–5.7]
  Home 17 1559 2164.1 7.8 [4.8–12.6] 0.0296
  Private Facility 20 2817 3885.8 5.1 [3.3–7.9] 0.4501

On comparison of cumulative survival functions, survival experiences were significantly different between infants exposed and not exposed to HIV (log rank p < 0.0001) (Fig 1).

Fig 1. Kaplan–Meier cumulative survival curve for infants exposed and not exposed to HIV.

Fig 1

Compared with that of infants not exposed to HIV, the adjusted hazard ratio (aHR) of child mortality was significantly greater for infants exposed to HIV (aHR: 5.6, 95% CI: 3.4–9.2), with a median survival time reduced by 70% (Table 3). Children born to mothers aged 15--24 years had a significantly greater hazard (aHR: 1.8, 95% CI: 1.1--2.9) than those born to mothers aged ≥25 years, with the median survival time reduced by 30%. There was a significantly greater hazard ratio (aHR: 1.8, 95% CI: 1.1--2.9) for mothers living without a partner than those living with a partner, with the median survival time ratio reduced by 30%. Home-delivered babies had a significantly greater hazard rate (aHR: 2.3; 95% CI: 1.3–4.0) than did those delivered in a public facility, with a reduced median survival time of 20%.

Table 3. Crude and adjusted times and hazard ratios for child mortality.

Crude Time Ratio [95%CI] Adj. Time Ratio [95%CI] Crude Weibull HR [95%CI] Adj.Weibull HR [95%CI]
Cohort
 HIV Unexposed 1 1
 HIV Exposed 0.4 [0.2–0.5] 0.3 [0.2–0.4] 4.1 [2.6–6.6] 5.6 [3.4–9.2]
Mother’s Age
 25 + years 1 1
 15-24 years 0.9 [0.7–1.3]] 0.7 [0.5–0.9] 1.1 [0.7–1.7] 1.8 [1.1–2.9]
Infant Sex
 Male 1 1
 Female 0.9 [0.7–1.3] 0.9 [0.7–1.2] 1.1 [0.7–1.7] 1.2 [0.7–1.8]
Family Social Economic Status
 High (4th or 5th quintile) 1 1
 Low (1st or 2nd quintile) 0.8 [0.5–1.2] 0.7 [0.4–1.0] 1.4 [0.8–2.4] 1.7 [1.0–3.0]
 Middle (3rd quintile) 0.8 [0.5–1.3] 0.7 [0.4–1.1] 1.4 [0.7–2.5] 1.6 [0.8–3.0]
Mother’s Marital Status
 Living with a partner 1 1
 Living without a partner 0.6 [0.4–0.9] 0.7 [0.5–0.9] 2.0 [1.2–3.4] 1.8 [1.1–2.9]
Mother’s Education
 Above Primary level 1 1
 None/Primary 1.0 [0.7–1.4] 1.0 [0.6–1.6]
Malaria in Pregnancy
 No 1 1
 Yes 1.0 [0.7–1.5] 0.9 [0.6–1.6]
Birth attendee
 Skilled 1 1
 Traditional birth attendants (TBA)/Other 0.7 [0.4–1.1] 1.9 [1.1–3.4]
Mode of transport to health facility
 Motorized 1 1
 Walking 0.8 [0.6–1.2] 0.8 [0.5–1.1] 1.3 [0.7–2.2] 1.5 [0.9–2.3]
Breastfeeding pattern
 Exclusive 1st 6 months 1 1
 Mixed/Replacement 1.0 [0.7–1.8] 1.0 [0.6–1.7] 1.0 [0.4–2.0] 1.0 [0.5–1.9]
Attended 4 or more ANC visits
 No 1 1
 Yes 1.1 [0.7–1.8] 1.1 [0.4–3.0]
ART Status (HIV infected only)
 Preconception 1 1
 During pregnancy 0.7 [0.4–1.3] 1.6 [0.7–3.5]
 Post delivery 0.6 [0.2–1.7] 1.7 [0.5–5.7]
Mother baseline Viral load non suppression(only Exposed)
 No 1 1
 Yes 0.8 [0.3–2.0] 1.4 [0.4–3.6]
Place of Delivery
 Public Facility 1 1
 Private Facility 0.9 [0.6–1.3] 0.8 [0.5–1.1] 1.2 [0.7–2.1] 1.4 [0.8–2.5]
 Home 0.6 [0.4–0.9] 0.8 [0.4–0.8] 1.9 [1.1–3.5] 2.3 [1.3–4.0]

The effective sample size was 11,514 and the bolded figures represent the significant variables.

The overall Weibull model shape parameter of p = 1.37 suggested that the hazard of child mortality generally increased with time.

Discussion

The overall mortality rate of 5.0 deaths per 1,000 person-years observed in the study cohort (with follow-up to 18 months) was six times lower than the 32.9 deaths per 1,000 person-years reported in a 2009–2011 cohort of children from rural Uganda over a median follow-up of 2 years [20]. Of note,in 2011 13.8% of children under five years of age were under weight with increased vulnerability to diesases; the infant and under-five mortality rates were 54/1000 and 90/1000 live births respectively with HIV prevalence at 7.3% [21,22]. The lower observed rate in this analysis could reflect that all infants in the study were engaged in health care regularly for study visits at the clinics where they could receive health education, vaccinations and child nutrition monitoring, which improved the quality of child health services and thus reduced the number of preventable child deaths [23]. Furthermore, infants exposed to HIV and their mothers had access to prevention of vertical transmission of HIV interventions, including maternal ART; the use of cotrimoxazole prophylaxis to prevent opportunistic infections, malaria, and upper respiratory infections; and the promotion of breastfeeding following the guidance of the World Health Organization (WHO) and Ministry of Health (MOH), which recommends a longer duration of breastfeeding instead of replacement feeding for infants exposed to HIV [2426].

In this study, an approximately fourfold greater child mortality rate was observed among infants exposed than among those not exposed to HIV. These findings are consistent with the available literature showing that infants exposed to HIV have higher mortality rates than those not exposed to HIV do, ranging from 4.0–13.6% [8,27,28]. This could be due to the infant feeding options available, such as exclusive breastfeeding or no breastfeeding, which poses different dilemmas. For example, longer breastfeeding may increase the vertical transmission of HIV and thus HIV-associated mortality, whereas shorter or no breastfeeding may expose the uninfected child to common illnesses such as pneumonia that lead to mortality [29,30]. Notably, there was no significant difference in mortality rates between exclusively breastfed infants and those receiving mixed or replacement feeding in the first 6 months, although studies have documented greater mortality rates among infants exposed than those not exposed to HIV with similar feeding patterns [8,31,32]. Other studies have shown that even after the introduction of prevention of vertical transmission of HIV policies and programs, infants exposed are at increased risk of severe bacterial infections, impaired cognitive function and death compared with those not exposed to HIV. While the causes of these poor outcomes are multifactorial, studies suggest that this could be attributed to the impaired innate and adaptive immune responses observed in infants exposed to HIV, secondary to ART exposure and maternal HIV infection [33,34].

A mother’s age of less than 25 years was a significant risk factor for child mortality, which is consistent with several studies that have shown associations between young maternal age and poor child survival [20,3539]. This is especially relevant for Uganda, with a teenage pregnancy rate of 25% and a high percentage of women under the age of 25 [40]. Young maternal age is associated with child mortality risk factors such as low birth weights, preterm deliveries, limited exposure to reproductive health and low maternal health-seeking behaviors, especially postnatal care [4043]. Low birth weight is a known risk factor for infant mortality and influences the health outcomes of newborns [44,45]. In this analysis, the absence of infant birthweight data precluded its inclusion in the analytical models. With the estimated unmet need for family planning at 30.4% among women aged 15--19 years in Uganda, strategies such as additional socioeconomic and educational support and meeting the family planning needs of young mothers may further reduce child mortality rates [35,40,4648].

In this analysis, both mothers living without a partner and those delivering an infant at home significantly increased the risk of child mortality. Nabongo et al., in their cohort study of children in rural Uganda, reported that the child’s birthplace, which was not a health facility, was associated with child mortality [20]. These factors could be markers of a lower socioeconomic status of the household [49]. Studies have revealed that low economic status is associated with infant mortality because it affects access to healthcare, nutrition, and social services [11,50,51]. The quality of health care received by the infant and mother is often determined by the place of delivery, with infants delivered at home not receiving the full package of postnatal care. Sarmistha provides new evidence that institutional delivery can significantly lower child mortality risk because it ensures effective and timely access to modern diagnostics and medical treatments to save lives [52]. While public health and treatment programs are in place to address the availability of healthcare services, interventions that enhance the economic well-being of the lower socioeconomic group might also have positive downstream impacts on child mortality. There were at least five limitations in this study. First, the total number of infant deaths identified was small, limiting the ability to perform regression analyses. Second, MIPs were recruited from child immunization clinics, creating selection bias in the sample. While immunization rates in Uganda are high, MIPs not engaging in early childhood care or engaging outside the enrollment age would not have been screened for participation in the study. The selection approach likely excluded children who were not immunized and were at high risk of mortality from vaccine-preventable diseases [53]. Therefore, the study population might have represented a healthier subset of the broader community, which potentially underestimated the true burden of mortality in the general population. Third, the study was not able to actively follow-up MIPs that were transferred to areas outside of the 152 study sites. As a result, transient MIPs may have been lost to follow-up. Fourth, selection bias could also have been introduced because of the study eligibility criteria, which excluded MIP due to severe illness of either the infant or the mother, mothers who were unable to give informed consent and those who refused the infant’s HIV antibody test at baseline. Finally, there were significant missing data for some of the critical variables, such as birth weight, due to a lack of source documents.

Mortality among infants exposed to HIV was significantly greater than that among those not exposed to HIV. Several factors, including HIV exposure, younger maternal age, the absence of a male partner, and home delivery of the child, increase the risk of mortality. Efforts to reduce child mortality could consider screening for these factors to be able to provide interventions during pregnancy and through the postpartum period for mothers whose children are at increased risk. Future studies are needed to explore how these factors drive mortality in this age group.

Supporting information

S1 Dataset. Mortality dataset used in analysis.

(XLS)

pone.0324122.s001.xls (2.4MB, xls)
S2 Data. Dictionary.

Varible descriptions within the mortality dataset.

(DOCX)

pone.0324122.s002.docx (20.6KB, docx)

Acknowledgments

The authors thank the prevention of vertical transmission of HIV impact evaluation study staff, study participants and health facility teams for their time and effort. All the authors contributed to the study design, study conduct, data analysis and interpretation, or manuscript writing.

The findings and conclusions in this manuscript are those of the author(s) and do not necessarily represent the official position of the funding agencies.

Data Availability

All relevant data are within the paper and its Supporting Information files.

Funding Statement

This research has been supported by the President's Emergency Plan for AIDS Relief (PEPFAR) through the Centers for Disease Control and Prevention (CDC) under the terms of cooperative agreement number 5U2G GH000817-02.

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Decision Letter 0

Emma Kalk

6 Dec 2024

PONE-D-24-43587Mortality rates in a cohort of infants attending immunization clinics in Uganda (2017–2019)PLOS ONE

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The authors present a review of infant/child mortality rates by HIV-exposure status of attendees at immunization clinics in Uganda in the context of a mature maternal HIV treatment programme. Mortality rates were significantly higher in infants/children of younger mother who were HIV exposed.

The manuscript is well-written but requires revision in preparation for publication.

1. Language. As noted by Reviewer 2, there is a move towards patient-centred language in the HIV field. Women living with HIV, prevention of vertical transmission of HIV etc. Please adjust all language in the title, abstract and manuscript.

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Additional Editor Comments:

The authors present a review of infant/child mortality rates by HIV-exposure status of attendees at immunization clinics in Uganda in the context of a mature maternal HIV treatment programme. Mortality rates were significantly higher in infants/children of younger mother who were HIV exposed.

The manuscript is well-written but requires revision in preparation for publication.

1. Language. As noted by Reviewer 2, there is a move towards patient-centred language in the HIV field. Women living with HIV, prevention of vertical transmission of HIV etc. Please adjust all language in the title, abstract and manuscript.

2. Please provide more detail with respect to the Methodology and Results as described by both reviewers.

3. Please consider review of the limitations in light of the reviewer comments.

4. In addition, there are further queries and clarifications noted by the reviewers which will strengthen the paper.

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Reviewer #1: Partly

Reviewer #2: Partly

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Reviewer #2: I Don't Know

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Reviewer #1: Yes

Reviewer #2: No

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Reviewer #2: Yes

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Here a list of suggestions:

- Abstract

-- Methods: The abstract should clarify where the study took place and the inclusion criteria for the participants. For example, were these women who brought their children to immunization clinics? This needs to be explicitly mentioned.

Additionally, the abstract should specify which variables were studied.

-- Conclusions: The conclusion about home delivery does not seem to be the most significant finding and could be reconsidered.

- Introduction

-- Confidence Intervals: It is unnecessary to include confidence intervals for descriptive data in this section (e.g., line 47). These figures are meant to provide context, and whether the estimate is 2.6 million or 3.1 million does not affect the overall argument. The same applies to line 53.

-- Option B+ Reference: On lines 69–71, is there a reference to support the introduction of Option B+ in Uganda? If not, this should be included.

-- HIV Prevalence: The introduction should explicitly include data on HIV prevalence in Uganda. The phrase "a country with a mature generalized HIV epidemic" is vague and should be clarified with specific prevalence data. How many people are affected? Why is it important to study HIV and infant mortality? These points should not be taken for granted, as the introduction must justify every aspect of the study design.

- Methods

-- S1 Text Reference: The reference to S1 Text is unclear. Is it a paper under evaluation for publication? If so, this should be explicitly stated. Citing a Word document is not appropriate for academic referencing. If the text is published, cite the published version. If it is under evaluation, clarify its status and provide more detail about its content.

-- Study Design and Sampling: The inclusion criteria and sampling methods need to be explained more clearly. For example, when and how were the women recruited? Were all women included? The methodology should provide a detailed explanation of how the study was conducted.

- Results

-- Table 1: Consider including tests of significance to identify differences between the samples of deceased and surviving participants.

-- Table 2: Similarly, tests of significance could be added here to improve the robustness of the analysis.

-- Key Findings: The paper primarily discusses "when" events occur (e.g., which groups have shorter survival times). However, it is unclear whether it also addresses "how many" events occur in each group (e.g., the absolute number or proportion of deaths or transmissions). To strengthen the results, I suggest additional analyses:

--- Significance testing: Compare the proportions of events (e.g., transmissions or deaths) between groups with different characteristics using chi-squared tests for categorical variables or t-tests/Mann-Whitney U tests for continuous variables.

--- Cumulative risk analysis: Include Kaplan-Meier survival curves and log-rank tests to analyze both the timing and the number of events.

--- Absolute data: Present the absolute number of events (e.g., transmissions or deaths) for each group to complement the findings on timing.

--- These additional analyses would address the critical question: do certain characteristics reduce the overall risk of death/transmission, or do they merely delay it?

- Discussion

-- Comparison with Older Data: Comparing the study sample with rural data from 15 years ago may not be the most appropriate choice. Are there more recent studies or datasets, such as World Bank data, that could provide a better comparison? If you decide to compare with the older study, include context about the previous cohort, such as HIV prevalence, maternal nutritional conditions, and other relevant factors.

-- Time in Care and Viral Load: It is surprising that time in care and viral load were not associated with the outcomes. This finding is inconsistent with existing evidence, which shows that longer time in care is associated with reduced neonatal infections and improved survival rates. If your findings diverge from this, it is essential to discuss why this might be the case.

-- Explore better limitations of the study related to selection bias. Another limitation of the study is the potential selection bias introduced by recruiting only mother-infant pairs attending immunization clinics. This approach likely excluded children who were not immunized and who may be at higher risk of mortality from vaccine-preventable diseases. As a result, the study population may represent a healthier subset of the broader community, potentially underestimating the true burden of mortality and transmission in the general population.

Reviewer #2: This manuscript describes child mortality rates, up to age 18 months, and associated risk factors, in Uganda, with a particular focus on comparing mortality rates by child HIV exposure status. It provides a valuable contribution to the field of research, particularly as the study period (2017 – 2018) coincided with the Universal ART era - a time marked by increased maternal access to ART and a reduction in vertical HIV transmission rates. Please consider addressing the following comments to help strengthen this manuscript.

Comments to authors:

General

1. General - The comparison of child mortality rates by HIV exposure status appears to be a main focus of this study, however this was not listed as one of the aims. Consider bringing this into the aims.

2. General – Language. Authors should be careful to use non stigmatizing person-first language. Consider infants who are exposed to HIV and infants unexposed to HIV instead of HIV exposed infants and HIV unexposed infants. Consider HIV vertical transmission prevention (VTP) instead of PMTCT.

3. General – Authors should consider carefully reviewing the manuscript for inconsistencies in spaces between words.

Abstract

4. Abstract – Line 31. Authors should consider adding that they used multivariate regression.

Introduction

5. Introduction - Line 53: 42 deaths (29-60) per 1,000 live births in 2021. Please specify if the (29-60) is a 95% CI.

6. Introduction – Line 65. Considering including and referencing Evans C, Chasekwa B, Ntozini R, Majo FD, Mutasa K, Tavengwa N, Mutasa B, Mbuya MNN, Smith LE, Stoltzfus RJ, Moulton LH, Humphrey JH, Prendergast AJ; Sanitation Hygiene Infant Nutrition Efficacy (SHINE) Trial Team. Mortality, Human Immunodeficiency Virus (HIV) Transmission, and Growth in Children Exposed to HIV in Rural Zimbabwe. Clin Infect Dis. 2021 Feb 16;72(4):586-594. doi: 10.1093/cid/ciaa076. PMID: 31974572; PMCID: PMC7884806.

7. Introduction – Check consistency in number of decimal places used throughout.

Methods

8. Methods – Which participants were excluded from the study?

9. Were mothers and children HEI tested for HIV at every visit? Is it possible that they weren’t tested and that there could have been misclassification of children HEI and HUI? If so, this should be discussed under limitations. Children HEI that die may have been living with HIV at the time of death. Children HUI also need to have been tested to be sure that they are not living with HIV. Although less common, children may acquire HIV horizontally.

10. Methods – Line 96. How was maternal ART status defined?

11. Methods – Line 115. Should “Wilcoxon log-rank test” just be log rank test?

12. Methods – Line 116. The authors state that they compared the differences in cumulative survival functions among HEIs and HUIs, however, these results were not shown in the results section.

13. Methods – Line 119. Authors should consider clarifying that they did Weibull proportional hazards regression and Weibull accelerated failure time regression (two different models).

14. Methods – Line 124. The authors should justify only using multiple imputation for variables with <10% missing values. What was done with variables that have >10% missing values and how did this affect your sample size for analyses?

Results

15. Results – Table 1. Authors should consider positioning HIV related variables (maternal viral load and maternal ART) together in the table.

16. Results – Table 1. For several of the variables (e.g. Feeding practice, maternal age, marital status) the reported proportions need to be revised as they are slightly off, e.g. the proportion of all mothers living with a partner should be 79.3% instead of 78.2%.

17. Under ART status, for the proportion of mothers who initiated during pregnancy, is this only among women who were diagnosed with HIV before pregnancy? Authors to consider a footnote to clarify.

18. Line 155 – Should this refer to cumulative probability or mortality rate? Consider ensuring the sentence doesn’t fall between Tables 1 and 2.

19. Table 2 – What does unweighted number refer to?

20. Table 2 - Consider positioning overall mortality above and separate from sex.

21. Table 3 – Include time ratios in the table caption.

22. Table 3 – What were the sample sizes for the adjusted models?

23. Table 3 – Consider a footnote for the table explaining why some of the estimates are bolded.

24. Line 169 – 170 – This figure refers to figure 1, but p=1.37 is not shown in the figure. Consider going into more detail about the results in Figure 1.

25. Figure 1 - It may be helpful to have a footnote explaining that the y axis has been scaled to be out of 1000.

26. Figure 1 – There are three smaller graphs. Two are stratified by mothers age and gender respectively and the third, showing cumulative probability of infant mortality/1000, is not stratified. It is unclear whether the third graph is meant to be a Kaplan Meier curve. Additionally, these three graphs were not mentioned in the methods section. If the authors choose to include the three small graphs, they need to be referred to in the methods section and more clearly explained in the figure caption.

Discussion

27. Discussion line 193 - “4.0-13.6”, are these deaths per 1000 person years?

28. Line 203 – “adoptive” should be “adaptive”

29. Discussion line 235 – These exclusion criteria need to be included in the methods section.

**********

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Reviewer #1: Yes:  Fausto Ciccacci

Reviewer #2: No

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While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool, https://pacev2.apexcovantage.com/ . PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Registration is free. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email PLOS at figures@plos.org . Please note that Supporting Information files do not need this step.

PLoS One. 2025 May 23;20(5):e0324122. doi: 10.1371/journal.pone.0324122.r003

Author response to Decision Letter 0


7 Mar 2025

Dear All,

Thank you for the comprehensive and constructive feedback you have given on our manuscript. All the support to make the manuscript better are much appreciated.

Below are my responses to the comments which have also been reflected in the resubmitted manuscript.

Sam

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Response: Noted

2. Thank you for stating the following financial disclosure: “This research has been supported by the President's Emergency Plan for AIDS Relief (PEPFAR) through the Centers for Disease Control and Prevention (CDC) under the terms of cooperative agreement number 5U2G GH000817-02.”

Please state what role the funders took in the study. If the funders had no role, please state: "The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript." If this statement is not correct you must amend it as needed. Please include this amended Role of Funder statement in your cover letter; we will change the online submission form on your behalf.

Response: Edited to reflect the amended role of the funder

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Response: The minimal anonymized data set has been shared.

4. Please include your full ethics statement in the ‘Methods’ section of your manuscript file. In your statement, please include the full name of the IRB or ethics committee who approved or waived your study, as well as whether or not you obtained informed written or verbal consent. If consent was waived for your study, please include this information in your statement as well.

Response: Full name of the IRB of record and the consent statement have been included under “Ethical considerations”

Additional Editor Comments:

The authors present a review of infant/child mortality rates by HIV-exposure status of attendees at immunization clinics in Uganda in the context of a mature maternal HIV treatment programme. Mortality rates were significantly higher in infants/children of younger mother who were HIV exposed.

The manuscript is well-written but requires revision in preparation for publication.

1. Language. As noted by Reviewer 2, there is a move towards patient-centered language in the HIV field. Women living with HIV, prevention of vertical transmission of HIV etc. Please adjust all language in the title, abstract and manuscript.

Response: The manuscript has been reviewed and the language edited to match the patient-centered language.

2. Please provide more detail with respect to the Methodology and Results as described by both reviewers.

Response: Edited to provide the details.

3. Please consider review of the limitations in light of the reviewer comments.

Response: Reviewed and edited to address the reviewer’s comments.

4. In addition, there are further queries and clarifications noted by the reviewers which will strengthen the paper.

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: Partly

Reviewer #2: Partly

________________________________________

2. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: No

Reviewer #2: I Don't Know

________________________________________

3. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: Yes

Reviewer #2: No

________________________________________

4. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: Yes

Reviewer #2: Yes

________________________________________

5. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1:

The manuscript covers an important topic, but certain methodological and interpretative issues need to be addressed to enhance clarity and rigor. Including additional significance testing, presenting absolute data on events, and expanding the discussion of unexpected findings would greatly strengthen the paper.

Response: Thank you for your time to comprehensively review our manuscript and the constructive feedback you have given. Below are my responses to the comments which have also been reflected in the resubmitted manuscript.

Here a list of suggestions:

Abstract

-- Methods: The abstract should clarify where the study took place and the inclusion criteria for the participants. For example, were these women who brought their children to immunization clinics? This needs to be explicitly mentioned.

Response: Edited and included.

Additionally, the abstract should specify which variables were studied.

Response: Edited and included.

-- Conclusions: The conclusion about home delivery does not seem to be the most significant finding and could be reconsidered.

Response: Reconsidered and Edited

Introduction

-- Confidence Intervals: It is unnecessary to include confidence intervals for descriptive data in this section (e.g., line 47). These figures are meant to provide context, and whether the estimate is 2.6 million or 3.1 million does not affect the overall argument. The same applies to line 53.

Response: Noted and Edited

-- Option B+ Reference: On lines 69–71, is there a reference to support the introduction of Option B+ in Uganda? If not, this should be included.

Response: Reference added

-- HIV Prevalence: The introduction should explicitly include data on HIV prevalence in Uganda. The phrase "a country with a mature generalized HIV epidemic" is vague and should be clarified with specific prevalence data. How many people are affected? Why is it important to study HIV and infant mortality? These points should not be taken for granted, as the introduction must justify every aspect of the study design.

Response: Noted and the content edited to address the comments.

Methods

-- S1 Text Reference: The reference to S1 Text is unclear. Is it a paper under evaluation for publication? If so, this should be explicitly stated. Citing a Word document is not appropriate for academic referencing. If the text is published, cite the published version. If it is under evaluation, clarify its status and provide more detail about its content.

Response: The paper is under evaluation for the publication. With your guidance, we have dropped the reference and edited the methods section to provide the methodology details.

-- Study Design and Sampling: The inclusion criteria and sampling methods need to be explained more clearly. For example, when and how were the women recruited? Were all women included? The methodology should provide a detailed explanation of how the study was conducted.

Response: We have edited the methods section to provide the missing details.

Results

-- Table 1: Consider including tests of significance to identify differences between the samples of deceased and surviving participants.

Response: Edited and included.

-- Table 2: Similarly, tests of significance could be added here to improve the robustness of the analysis.

Response: Done

-- Key Findings: The paper primarily discusses "when" events occur (e.g., which groups have shorter survival times). However, it is unclear whether it also addresses "how many" events occur in each group (e.g., the absolute number or proportion of deaths or transmissions). To strengthen the results, I suggest additional analyses:

Response: Additional analysis done, and a table has been added to figure 1

--- Significance testing: Compare the proportions of events (e.g., transmissions or deaths) between groups with different characteristics using chi-squared tests for categorical variables or t-tests/Mann-Whitney U tests for continuous variables.

Response: Additional analysis done, and p-values added to the tables 1 and 2

--- Cumulative risk analysis: Include Kaplan-Meier survival curves and log-rank tests to analyze both the timing and the number of events.

Response: Figure 1 revised to include the suggestions.

--- Absolute data: Present the absolute number of events (e.g., transmissions or deaths) for each group to complement the findings on timing.

Response: Done and included in figure 1

--- These additional analyses would address the critical question: do certain characteristics reduce the overall risk of death/transmission, or do they merely delay it?

Response: Additional analyses have been done as guided above. Of note there was violation of Cox proportional hazards assumptions by most of the independent variables, thus the accelerated failure time model (ACT) was used as the alternative. Without the use of the Cox proportional hazards model, we could not assess how various covariates influence the hazard rate to help with identifying whether a characteristic reduces the risk or merely delays the event.

Discussion

-- Comparison with Older Data: Comparing the study sample with rural data from 15 years ago may not be the most appropriate choice. Are there more recent studies or datasets, such as World Bank data, that could provide a better comparison? If you decide to compare with the older study, include context about the previous cohort, such as HIV prevalence, maternal nutritional conditions, and other relevant factors.

Response: The two cohorts have a 6-year difference (2009/11 and 2017/19) and not 15 years. Yes, there are recent statistics, but they are more about infant mortality rates and under 5 mortality rates which are not comparable to our 2 years follow up period. We have added context of the 2009/11 cohort in the text as guided.

-- Time in Care and Viral Load: It is surprising that time in care and viral load were not associated with the outcomes. This finding is inconsistent with existing evidence, which shows that longer time in care is associated with reduced neonatal infections and improved survival rates. If your findings diverge from this, it is essential to discuss why this might be the case.

Response: Yes, time in care and viral load were not associated with the main outcome (Child Mortality) since time in care and viral load captured were for the mother and not the child. If these were for the child, then it would be diverging from the existing evidence.

-- Explore better limitations of the study related to selection bias. Another limitation of the study is the potential selection bias introduced by recruiting only mother-infant pairs attending immunization clinics. This approach likely excluded children who were not immunized and who may be at higher risk of mortality from vaccine-preventable diseases. As a result, the study population may represent a healthier subset of the broader community, potentially underestimating the true burden of mortality and transmission in the general population.

Response: Suggestion accepted, and the limitation section of the discussion has been edited to reflect it.

Reviewer #2:

This manuscript describes child mortality rates, up to age 18 months, and associated risk factors, in Uganda, with a particular focus on comparing mortality rates by child HIV exposure status. It provides a valuable contribution to the field of research, particularly as the study period (2017 – 2018) coincided with the Universal ART era - a time marked by increased maternal access to ART and a reduction in vertical HIV transmission rates. Please consider addressing the following comments to help strengthen this manuscript.

Comments to authors:

General

1. General - The comparison of child mortality rates by HIV exposure status appears to be a main focus of this study, however this was not listed as one of the aims. Consider bringing this into the aims.

2. General – Language. Authors should be careful to use non stigmatizing person-first language. Consider infants who are exposed to HIV and infants unexposed to HIV instead of HIV exposed infants and HIV unexposed infants. Consider HIV vertical transmission prevention (VTP) instead of PMTCT.

3. General – Authors should consider carefully reviewing the manuscript for inconsistencies in spaces between words.

Response: Thank you for your time to comprehensively review our manuscript and the constructive feedback you have given. Below are my responses to the comments which have also been reflected in the resubmitted manuscript.

Abstract

4. Abstract – Line 31. Authors should consider adding that they used multivariate regression.

Response: Added.

Introduction

5. Introduction - Line 53: 42 deaths (29-60) per 1,000 live births in 2021. Please specify if the (29-60) is a 95% CI.

Response: Yes, they are the 95% CI. I have deleted them as recommended by reviewer # 1.

6. Introduction – Line 65. Considering including and referencing Evans C, Chasekwa B, Ntozini R, Majo FD, Mutasa K, Tavengwa N, Mutasa B, Mbuya MNN, Smith LE, Stoltzfus RJ, Moulton LH, Humphrey JH, Prendergast AJ; Sanitation Hygiene Infant Nutrition Efficacy (SHINE) Trial Te

Attachment

Submitted filename: Response to Reviewers.docx

pone.0324122.s004.docx (28.2KB, docx)

Decision Letter 1

Emma Kalk

14 Mar 2025

PONE-D-24-43587R1Mortality rates in a cohort of infants attending immunization clinics in Uganda (2017–2019)PLOS ONE

Dear Dr. Sendagala,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

Please submit your revised manuscript by Apr 28 2025 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org . When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

Please include the following items when submitting your revised manuscript:

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If you would like to make changes to your financial disclosure, please include your updated statement in your cover letter. Guidelines for resubmitting your figure files are available below the reviewer comments at the end of this letter.

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We look forward to receiving your revised manuscript.

Kind regards,

Emma K. Kalk

Academic Editor

PLOS ONE

Journal Requirements:

Please review your reference list to ensure that it is complete and correct. If you have cited papers that have been retracted, please include the rationale for doing so in the manuscript text, or remove these references and replace them with relevant current references. Any changes to the reference list should be mentioned in the rebuttal letter that accompanies your revised manuscript. If you need to cite a retracted article, indicate the article’s retracted status in the References list and also include a citation and full reference for the retraction notice.

Additional Editor Comments:

“Noted and edited” is not an adequate response to comments. It makes it very time consuming to review the revision. The changes should be included in the table and the new page and line noted.

Please spell out abbreviations the first they appear in both the abstract and manuscript.

Line 35: timing of mother’s ART initiation?

Line 77: are these infants exposed to HIV AND uninfected?

Line 80: does “young female sex” refer to the mothers? In this context I assume that all mothers are female which doesn’t make sense as a risk factor.

Line 96: HEI and HUI haven’t been previously defined.

Line 107: mothers is repeated in brackets.

How was SES determined?

Lines 195-196 and 197-199 are exact repeats of the same sentences.

Line 216: what is the difference between mothers living without a partner and single mothers?

Methods – Line 116. The authors state that they compared the differences in

cumulative survival functions among HEIs and HUIs, however, these results were not

shown in the results section.

Table 3 –The effective sample size was 11514. Can you include this as a footnote?

[Note: HTML markup is below. Please do not edit.]

[NOTE: If reviewer comments were submitted as an attachment file, they will be attached to this email and accessible via the submission site. Please log into your account, locate the manuscript record, and check for the action link "View Attachments". If this link does not appear, there are no attachment files.]

While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool, https://pacev2.apexcovantage.com/ . PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Registration is free. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email PLOS at figures@plos.org . Please note that Supporting Information files do not need this step.

PLoS One. 2025 May 23;20(5):e0324122. doi: 10.1371/journal.pone.0324122.r005

Author response to Decision Letter 1


14 Apr 2025

Journal Requirements:

Please review your reference list to ensure that it is complete and correct. If you have cited papers that have been retracted, please include the rationale for doing so in the manuscript text or remove these references and replace them with relevant current references. Any changes to the reference list should be mentioned in the rebuttal letter that accompanies your revised manuscript. If you need to cite a retracted article, indicate the article’s retracted status in the References list and include a citation and full reference for the retraction notice.

Response: All references are up to date. Done changes to

Ref 2: Updated the access link to the current URL (Line 336-337).

Ref 15: Changed to the current updated guidelines of 2021 instead of 2014 (Line 370-372).

Additional Editor Comments:

“Noted and edited” is not an adequate response to comments. It makes it very time consuming to review the revision. The changes should be included in the table and the new page and line noted.

Response: Thank you for guidance. We have edited the responses to match the guidance and added the new line.

Please spell out abbreviations the first they appear in both the abstract and manuscript.

Response: Reviewed the manuscript and all abbreviations spelt out on initial use.

Line 35: timing of mother’s ART initiation?

Response: Deleted “timing of” (Line 36)

Line 77: are these infants exposed to HIV AND uninfected?

Response: They were infants exposed to HIV and uninfected. Added “but not infected” (Line 78)

Line 80: does “young female sex” refer to the mothers? In this context I assume that all mothers are female which doesn’t make sense as a risk factor.

Response: Deleted female sex (Line 82)

Line 96: HEI and HUI haven’t been previously defined.

Response: To match the patient-centered language in the HIV field, deleted HEI and HUI and replaced with “infants exposed and not exposed to HIV” (Line 98)

Line 107: mothers is repeated in brackets.

Response: Deleted the brackets (Line 109)

How was SES determined?

Response: Deleted “socioeconomic status by quintiles” since it was a derived variable (Line 128).

Included a sentence on how the SES was derived (Line 131-132).

Lines 195-196 and 197-199 are exact repeats of the same sentences.

Response: Deleted line 197-199 and retained line 195-196 (currently Line 198-199)

Line 216: what is the difference between mothers living without a partner and single mothers?

Response: There is no difference and for clarity deleted “single mothers” and replaced with “those living with a partner” (Line 222).

Methods – Line 116. The authors state that they compared the differences in

cumulative survival functions among HEIs and HUIs, however, these results were not

shown in the results section.

Response: Results section edited to include the results (Line 210-212)

Table 3 –The effective sample size was 11514. Can you include this as a footnote?

Response: It has been included as a foot note under table 3 (Line 233).

Attachment

Submitted filename: Response_to_Reviewers_auresp_2.docx

pone.0324122.s005.docx (33.7KB, docx)

Decision Letter 2

Emma Kalk

22 Apr 2025

Mortality rates in a cohort of infants attending immunization clinics in Uganda (2017–2019)

PONE-D-24-43587R2

Dear Dr. Sendagala,

We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.

Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication.

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Acceptance letter

Emma Kalk

PONE-D-24-43587R2

PLOS ONE

Dear Dr. Sendagala,

I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now being handed over to our production team.

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Academic Editor

PLOS ONE

Associated Data

    This section collects any data citations, data availability statements, or supplementary materials included in this article.

    Supplementary Materials

    S1 Dataset. Mortality dataset used in analysis.

    (XLS)

    pone.0324122.s001.xls (2.4MB, xls)
    S2 Data. Dictionary.

    Varible descriptions within the mortality dataset.

    (DOCX)

    pone.0324122.s002.docx (20.6KB, docx)
    Attachment

    Submitted filename: Response to Reviewers.docx

    pone.0324122.s004.docx (28.2KB, docx)
    Attachment

    Submitted filename: Response_to_Reviewers_auresp_2.docx

    pone.0324122.s005.docx (33.7KB, docx)

    Data Availability Statement

    All relevant data are within the paper and its Supporting Information files.


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