Predictive modeling for infectious diarrheal disease in pediatric populations: A systematic review.

Introduction: Diarrhea is still a significant global public health problem. There are currently no systematic evaluation of the modeling areas and approaches to predict diarrheal illness outcomes. This paper reviews existing research efforts in predictive modeling of infectious diarrheal illness in pediatric populations. Methods: We conducted a systematic review via a PubMed search for the period 1990-2021. A comprehensive search query was developed through an iterative process and literature on predictive modeling of diarrhea was retrieved. The following filters were applied to the search results: human subjects, English language, and children (birth to 18 years). We carried out a narrative synthesis of the included publications. Results: Our literature search returned 2671 articles. After manual evaluation, 38 of these articles were included in this review. The most common research topic among the studies were disease forecasts 14 (36.8%), vaccine-related predictions 9 (23.7%), and disease/pathogen detection 5 (13.2%). Majority of these studies were published between 2011 and 2020, 28 (73.7%). The most common technique used in the modeling was machine learning 12 (31.6%) with various algorithms used for the prediction tasks. With change in the landscape of diarrheal etiology after rotavirus vaccine introduction, many open areas (disease forecasts, disease detection, and strain dynamics) remain for pathogen-specific predictive models among etiological agents that have emerged as important. Additionally, the outcomes of diarrheal illness remain under researched. We also observed lack of consistency in the reporting of results of prediction models despite the available guidelines highlighting the need for common data standards and adherence to guidelines on reporting of predictive models for biomedical research. Conclusions: Our review identified knowledge gaps and opportunities in predictive modeling for diarrheal illness, and limitations in existing attempts whilst advancing some precursory thoughts on how to address them, aiming to invigorate future research efforts in this sphere.

Genetic and potential antigenic evolution of influenza A(H1N1)pdm09 viruses circulating in Kenya during 2009-2018 influenza seasons.

Influenza viruses undergo rapid evolutionary changes, which requires continuous surveillance to monitor for genetic and potential antigenic changes in circulating viruses that can guide control and prevention decision making. We sequenced and phylogenetically analyzed A(H1N1)pdm09 virus genome sequences obtained from specimens collected from hospitalized patients of all ages with or without pneumonia between 2009 and 2018 from seven sentinel surveillance sites across Kenya. We compared these sequences with recommended vaccine strains during the study period to infer genetic and potential antigenic changes in circulating viruses and associations of clinical outcome. We generated and analyzed a total of 383 A(H1N1)pdm09 virus genome sequences. Phylogenetic analyses of HA protein revealed that multiple genetic groups (clades, subclades, and subgroups) of A(H1N1)pdm09 virus circulated in Kenya over the study period; these evolved away from their vaccine strain, forming clades 7 and 6, subclades 6C, 6B, and 6B.1, and subgroups 6B.1A and 6B.1A1 through acquisition of additional substitutions. Several amino acid substitutions among circulating viruses were associated with continued evolution of the viruses, especially in antigenic epitopes and receptor binding sites (RBS) of circulating viruses. Disease severity declined with an increase in age among children aged < 5 years. Our study highlights the necessity of timely genomic surveillance to monitor the evolutionary changes of influenza viruses. Routine influenza surveillance with broad geographic representation and whole genome sequencing capacity to inform on prioritization of antigenic analysis and the severity of circulating strains are critical to improved selection of influenza strains for inclusion in vaccines.

Correcting for measurement error in assessing gestational age in a low-resource setting: a regression calibration approach.

Introduction: Measurement error in gestational age (GA) may bias the association of GA with a health outcome. Ultrasound-based GA is considered the gold standard and is not readily available in low-resource settings. We corrected for measurement error in GA based on fundal height (FH) and date of last menstrual period (LMP) using ultrasound from the sub-cohort and adjusted for the bias in associating GA with neonatal mortality and low birth weight (< 2,500 grams, LBW). Methods: We used data collected from 01/2015 to 09/2019 from pregnant women enrolled at two public hospitals in Siaya county, Kenya (N = 2,750). We used regression calibration to correct for measurement error in FH- and LMP-based GA accounting for maternal and child characteristics. We applied logistic regression to associate GA with neonatal mortality and low birth weight, with and without calibrating FH- and LMP-based GA. Results: Calibration improved the precision of LMP (correlation coefficient, ρ from 0.48 to 0.57) and FH-based GA (ρ from 0.82 to 0.83). Calibrating FH/LMP-based GA eliminated the bias in the mean GA estimates. The log odds ratio that quantifies the association of GA with neonatal mortality increased by 29% (from -0.159 to -0.205) by calibrating FH-based GA and by more than twofold (from -0.158 to -0.471) by calibrating LMP-based GA. Conclusion: Calibrating FH/LMP-based GA improved the accuracy and precision of GA estimates and strengthened the association of GA with neonatal mortality/LBW. When assessing GA, neonatal public health and clinical interventions may benefit from calibration modeling in settings where ultrasound may not be fully available.

Assessment of gestational age at antenatal care visits among Kenyan women to inform delivery of a maternal respiratory syncytial virus (RSV) vaccine in low- and middle-income countries.

Background: Maternal respiratory syncytial virus (RSV) vaccines that are likely to be implementable in low- and middle-income countries (LMICs) are in final stages of clinical trials. Data on the number of women presenting for antenatal care (ANC) per day and proportion attending within the proposed gestational window for vaccine delivery, is a prerequisite to guide development of vaccine vial size and inform vaccine uptake in this setting. Methods: We undertook administrative review and abstraction of ANC attendance records from 2019 registers of 24 selected health facilities, stratified by the level of care, from Kilifi, Siaya and Nairobi counties in Kenya. Additional data were obtained from Mother and Child Health (MCH) booklets of women in each of the Health and Demographic Surveillance System (HDSS) areas of Kilifi, Nairobi and Siaya. Data analysis involved descriptive summaries of the number (mean, median) and proportion of women attending ANC within the gestational window period of 28-32 weeks and 24-36 weeks. Results: A total of 62,153 ANC records were abstracted, 33,872 from Kilifi, 19,438 from Siaya and 8,943 from Nairobi Counties. The median (Interquartile range, IQR) number of women attending ANC per day at a gestational age window of 28-32 and 24-36 weeks, respectively, were: 4 (2-6) and 7 (4-12) in dispensaries, 5 (2-9) and 10 (4-19) in health centres and 6 (4-11) and 16 (10-26) in county referral hospitals. In the HDSS areas of Kilifi, Siaya and Nairobi, pregnant women attending at least one ANC visit, within a window of 28-32 weeks, were: 77% (360/470), 75% (590/791) and 67% (547/821), respectively. Conclusions: About 70% of pregnant women across three distinct geographical regions in Kenya, attend ANC within 28-32 weeks of gestation. A multidose vial size with about five doses per vial, approximates daily ANC attendance and would not incur possible wastage in similar settings.

Value profile for respiratory syncytial virus vaccines and monoclonal antibodies.

Respiratory syncytial virus (RSV) is the predominant cause of acute lower respiratory infection (ALRI) in young children worldwide, yet no licensed RSV vaccine exists to help prevent the millions of illnesses and hospitalizations and tens of thousands of young lives taken each year. Monoclonal antibody (mAb) prophylaxis exists for prevention of RSV in a small subset of very high-risk infants and young children, but the only currently licensed product is impractical, requiring multiple doses and expensive for the low-income settings where the RSV disease burden is greatest. A robust candidate pipeline exists to one day prevent RSV disease in infant and pediatric populations, and it focuses on two promising passive immunization approaches appropriate for low-income contexts: maternal RSV vaccines and long-acting infant mAbs. Licensure of one or more candidates is feasible over the next one to three years and, depending on final product characteristics, current economic models suggest both approaches are likely to be cost-effective. Strong coordination between maternal and child health programs and the Expanded Program on Immunization will be needed for effective, efficient, and equitable delivery of either intervention. This 'Vaccine Value Profile' (VVP) for RSV is intended to provide a high-level, holistic assessment of the information and data that are currently available to inform the potential public health, economic and societal value of pipeline vaccines and vaccine-like products. This VVP was developed by a working group of subject matter experts from academia, non-profit organizations, public private partnerships and multi-lateral organizations, and in collaboration with stakeholders from the WHO headquarters. All contributors have extensive expertise on various elements of the RSV VVP and collectively aimed to identify current research and knowledge gaps. The VVP was developed using only existing and publicly available information.

Respiratory Syncytial Virus (RSV) Disease and Prevention Products: Knowledge, Attitudes, and Preferences of Kenyan Healthcare Workers in Two Counties in 2021.

Respiratory syncytial virus (RSV) is a major cause of lower respiratory tract infection (LRTI) among infants under 6 months of age. Yet, in Kenya, little is known about healthcare workers' (HCWs) knowledge, attitudes, and perceptions around RSV disease and the prevention products under development. Between September and October 2021, we conducted a mixed methods cross-sectional survey to assess HCWs' knowledge, attitudes, and perceptions of RSV disease and RSV vaccinations in two counties. We enrolled HCWs delivering services directly at maternal and child health (MCH) departments in selected health facilities (frontline HCWs) and health management officers (HMOs). Of the 106 respondents, 94 (88.7%) were frontline HCWs, while 12 were HMOs. Two of the HMOs were members of the Kenya National Immunization Technical Advisory Group (KENITAG). Of the 104 non-KENITAG HCWs, only 41 (39.4%) had heard about RSV disease, and 38/41 (92.7%) felt that pregnant women should be vaccinated against RSV. Most participants would recommend a single-dose vaccine schedule (n = 62, 58.5%) for maximal adherence and compliance (n = 38/62, 61.3%), single dose/device vaccines (n = 50/86, 58.1%) to prevent wastage and contamination, and maternal vaccination through antenatal care clinics (n = 53, 50%). We found the need for increased knowledge about RSV disease and prevention among Kenyan HCWs.

Malaria, climate variability, and interventions: modelling transmission dynamics.

Assessment of the relative impact of climate change on malaria dynamics is a complex problem. Climate is a well-known factor that plays a crucial role in driving malaria outbreaks in epidemic transmission areas. However, its influence in endemic environments with intensive malaria control interventions is not fully understood, mainly due to the scarcity of high-quality, long-term malaria data. The demographic surveillance systems in Africa offer unique platforms for quantifying the relative effects of weather variability on the burden of malaria. Here, using a process-based stochastic transmission model, we show that in the lowlands of malaria endemic western Kenya, variations in climatic factors played a key role in driving malaria incidence during 2008-2019, despite high bed net coverage and use among the population. The model captures some of the main mechanisms of human, parasite, and vector dynamics, and opens the possibility to forecast malaria in endemic regions, taking into account the interaction between future climatic conditions and intervention scenarios.

Estimates of the national burden of respiratory syncytial virus in Kenyan children aged under 5 years, 2010-2018.

BACKGROUND: Respiratory syncytial virus (RSV) is among the leading childhood causes of viral pneumonia worldwide. Establishing RSV-associated morbidity and mortality is important in informing the development, delivery strategies, and evaluation of interventions. METHODS: Using data collected during 2010-2018 from base regions (population-based surveillance studies in western Kenya and the Kilifi Health and Demographic Surveillance Study), we estimated age-specific rates of acute respiratory illness (ARI), severe acute respiratory illness (SARI-defined as hospitalization with cough or difficulty breathing with onset within the past 10 days), and SARI-associated deaths. We extrapolated the rates from the base regions to other regions of Kenya, while adjusting for risk factors of ARI and healthcare seeking behavior, and finally applied the proportions of RSV-positive cases identified from various sentinel and study facilities to the rates to obtain regional age-specific rates of RSV-associated outpatient and non-medically attended ARI and hospitalized SARI and severe ARI that was not hospitalized (non-hospitalized SARI). We applied age-specific RSV case fatality ratios to SARI to obtain estimates of RSV-associated in- and out-of-hospital deaths. RESULTS: Among Kenyan children aged < 5 years, the estimated annual incidence of outpatient and non-medically attended RSV-associated ARI was 206 (95% credible interval, CI; 186-229) and 226 (95% CI; 204-252) per 1000 children, respectively. The estimated annual rates of hospitalized and non-hospitalized RSV-associated SARI were 349 (95% CI; 303-404) and 1077 (95% CI; 934-1247) per 100,000 children respectively. The estimated annual number of in- and out-of-hospital deaths associated with RSV infection in Kenya were 539 (95% CI; 420-779) and 1921 (95% CI; 1495-2774), respectively. Children aged < 6 months had the highest burden of RSV-associated severe disease: 2075 (95% CI; 1818-2394) and 44 (95% CI 25-71) cases per 100,000 children for hospitalized SARI and in-hospital deaths, respectively. CONCLUSIONS: Our findings suggest a substantial disease burden due to RSV infection, particularly among younger children. Prioritizing development and use of maternal vaccines and affordable long-lasting monoclonal antibodies could help reduce this burden.

The relative effect of climate variability on malaria incidence after scale-up of interventions in western Kenya: A time-series analysis of monthly incidence data from 2008 to 2019.

Background: Despite considerable progress made over the past 20 years in reducing the global burden of malaria, the disease remains a major public health problem and there is concern that climate change might expand suitable areas for transmission. This study investigated the relative effect of climate variability on malaria incidence after scale-up of interventions in western Kenya. Methods: Bayesian negative binomial models were fitted to monthly malaria incidence data, extracted from records of patients with febrile illnesses visiting the Lwak Mission Hospital between 2008 and 2019. Data pertaining to bed net use and socio-economic status (SES) were obtained from household surveys. Climatic proxy variables obtained from remote sensing were included as covariates in the models. Bayesian variable selection was used to determine the elapsing time between climate suitability and malaria incidence. Results: Malaria incidence increased by 50% from 2008 to 2010, then declined by 73% until 2015. There was a resurgence of cases after 2016, despite high bed net use. Increase in daytime land surface temperature was associated with a decline in malaria incidence (incidence rate ratio [IRR] = 0.70, 95% Bayesian credible interval [BCI]: 0.59-0.82), while rainfall was associated with increased incidence (IRR = 1.27, 95% BCI: 1.10-1.44). Bed net use was associated with a decline in malaria incidence in children aged 6-59 months (IRR = 0.78, 95% BCI: 0.70-0.87) but not in older age groups, whereas SES was not associated with malaria incidence in this population. Conclusions: Variability in climatic factors showed a stronger effect on malaria incidence than bed net use. Bed net use was, however, associated with a reduction in malaria incidence, especially among children aged 6-59 months after adjusting for climate effects. To sustain the downward trend in malaria incidence, this study recommends continued distribution and use of bed nets and consideration of climate-based malaria early warning systems when planning for future control interventions.

Healthcare-seeking behavior for respiratory illnesses in Kenya: implications for burden of disease estimation.

BACKGROUND: Understanding healthcare-seeking patterns for respiratory illness can help improve estimation of disease burden and target public health interventions to control acute respiratory disease in Kenya. METHODS: We conducted a cross-sectional survey to determine healthcare utilization patterns for acute respiratory illness (ARI) and severe pneumonia in four diverse counties representing urban, peri-urban, rural mixed farmers, and rural pastoralist communities in Kenya using a two-stage (sub-locations then households) cluster sampling procedure. Healthcare seeking behavior for ARI episodes in the last 14 days, and severe pneumonia in the last 12 months was evaluated. Severe pneumonia was defined as reported cough and difficulty breathing for > 2 days and report of hospitalization or recommendation for hospitalization, or a danger sign (unable to breastfeed/drink, vomiting everything, convulsions, unconscious) for children < 5 years, or report of inability to perform routine chores. RESULTS: From August through September 2018, we interviewed 28,072 individuals from 5,407 households. Of those surveyed, 9.2% (95% Confidence Interval [CI] 7.9-10.7) reported an episode of ARI, and 4.2% (95% CI 3.8-4.6) reported an episode of severe pneumonia. Of the reported ARI cases, 40.0% (95% CI 36.8-43.3) sought care at a health facility. Of the74.2% (95% CI 70.2-77.9) who reported severe pneumonia and visited a medical health facility, 28.9% (95% CI 25.6-32.6) were hospitalized and 7.0% (95% CI 5.4-9.1) were referred by a clinician to the hospital but not hospitalized. 21% (95% CI 18.2-23.6) of self-reported severe pneumonias were hospitalized. Children aged < 5 years and persons in households with a higher socio-economic status were more likely to seek care for respiratory illness at a health facility. CONCLUSION: Our findings suggest that hospital-based surveillance captures less than one quarter of severe pneumonia in the community. Multipliers from community household surveys can account for underutilization of healthcare resources and under-ascertainment of severe pneumonia at hospitals.

Rhinovirus dynamics across different social structures.

Rhinoviruses (RV), common human respiratory viruses, exhibit significant antigenic diversity, yet their dynamics across distinct social structures remain poorly understood. Our study delves into RV dynamics within Kenya by analysing VP4/2 sequences across four different social structures: households, a public primary school, outpatient clinics in the Kilifi Health and Demographics Surveillance System (HDSS), and countrywide hospital admissions and outpatients. The study revealed the greatest diversity of RV infections at the countrywide level (114 types), followed by the Kilifi HDSS (78 types), the school (47 types), and households (40 types), cumulatively representing >90% of all known RV types. Notably, RV diversity correlated directly with the size of the population under observation, and several RV type variants occasionally fuelled RV infection waves. Our findings highlight the critical role of social structures in shaping RV dynamics, information that can be leveraged to enhance public health strategies. Future research should incorporate whole-genome analysis to understand fine-scale evolution across various social structures.

Drivers of respiratory syncytial virus seasonal epidemics in children under 5 years in Kilifi, coastal Kenya.

Respiratory syncytial virus (RSV) causes significant childhood morbidity and mortality in the developing world. The determinants of RSV seasonality are of importance in designing interventions. They are poorly understood in tropical and sub-tropical regions in low- and middle-income countries. Our study utilized long-term surveillance data on cases of RSV associated with severe or very severe pneumonia in children aged 1 day to 59 months admitted to the Kilifi County Hospital. A generalized additive model was used to investigate the association between RSV admissions and meteorological variables (maximum temperature, rainfall, absolute humidity); weekly number of births within the catchment population; and school term dates. Furthermore, a time-series-susceptible-infected-recovered (TSIR) model was used to reconstruct an empirical transmission rate which was used as a dependent variable in linear regression and generalized additive models with meteorological variables and school term dates. Maximum temperature, absolute humidity, and weekly number of births were significantly associated with RSV activity in the generalized additive model. Results from the TSIR model indicated that maximum temperature and absolute humidity were significant factors. Rainfall and school term did not yield significant relationships. Our study indicates that meteorological parameters and weekly number of births potentially play a role in the RSV seasonality in this region. More research is required to explore the underlying mechanisms underpinning the observed relationships.

Comparable Pregnancy Outcomes for HIV-Uninfected and HIV-Infected Women on Antiretroviral Treatment in Kenya.

BACKGROUND: The impact of human immunodeficiency virus (HIV) on pregnancy outcomes for women on antiretroviral therapy (ART) in sub-Saharan Africa remains unclear. METHODS: Pregnant women in Kenya were enrolled in the second trimester and followed up to delivery. We estimated effects of treated HIV with 3 pregnancy outcomes: loss, premature birth, and low birth weight and factors associated with HIV-positive status. RESULTS: Of 2113 participants, 311 (15%) were HIV infected and on ART. Ninety-one of 1762 (5%) experienced a pregnancy loss, 169/1725 (10%) a premature birth (<37 weeks), and 74/1317 (6%) had a low-birth-weight newborn (<2500 g). There was no evidence of associations between treated HIV infection and pregnancy loss (adjusted relative risk [aRR], 1.19; 95% confidence interval [CI], .65-2.16; P = .57), prematurity (aRR, 1.09; 95% CI, .70-1.70; P = .69), and low birth weight (aRR, 1.36; 95% CI, .77-2.40; P = .27). Factors associated with an HIV-positive status included older age, food insecurity, lower education level, higher parity, lower gestation at first antenatal clinic, anemia, and syphilis. Women who were overweight or underweight were less likely to be HIV infected compared to those with normal weight. CONCLUSIONS: Currently treated HIV was not significantly associated with adverse pregnancy outcomes. HIV-infected women, however, had a higher prevalence of other factors associated with adverse pregnancy outcomes.

The burden of influenza among Kenyan pregnant and postpartum women and their infants, 2015-2020.

BACKGROUND: In tropical Africa, data about influenza-associated illness burden are needed to assess potential benefits of influenza vaccination among pregnant women. We estimated the incidence of influenza among pregnant women and their infants in Siaya County, Kenya. METHODS: We enrolled women at <31 weeks of gestation and conducted weekly follow-up until 6-month postpartum to identify acute respiratory illnesses (ARIs). We defined ARI among mothers as reported cough, rhinorrhoea or sore throat and among infants as maternal-reported cough, difficulty breathing, rhinorrhoea or clinician diagnosis of respiratory illness. We collected nasal/nasopharyngeal and oropharyngeal swabs from mothers/infants with ARI and tested for influenza A and B using molecular assays. We calculated antenatal incidence of laboratory-confirmed influenza among mothers and postnatal incidence among mothers and infants. RESULTS: During June 2015 to May 2020, we analysed data from 3,026 pregnant women at a median gestational age of 16 weeks (interquartile range [IQR], 13, 18) and followed 2,550 infants. Incidence of laboratory-confirmed influenza during pregnancy (10.3 episodes per 1,000 person-months [95% confidence interval {CI} 8.6-11.8]) was twofold higher than in the postpartum period (4.0 [95% CI 2.6-5.5]; p < 0.01). Incidence was significantly higher among human immunodeficiency virus (HIV)-infected pregnant women (15.6 [95% CI 11.0-20.6] vs. 9.1 [95% CI 7.5-10.8]; p < 0.01). Incidence among young infants was 4.4 (95% CI 3.0-5.9) and similar among HIV-exposed and HIV-unexposed infants. CONCLUSION: Our findings suggest a substantial burden of influenza illnesses during pregnancy, with a higher burden among HIV-infected mothers. Kenyan authorities should consider the value of vaccinating pregnant women, especially if HIV infected.

Malaria hospitalisation in East Africa: age, phenotype and transmission intensity.

BACKGROUND: Understanding the age patterns of disease is necessary to target interventions to maximise cost-effective impact. New malaria chemoprevention and vaccine initiatives target young children attending routine immunisation services. Here we explore the relationships between age and severity of malaria hospitalisation versus malaria transmission intensity. METHODS: Clinical data from 21 surveillance hospitals in East Africa were reviewed. Malaria admissions aged 1 month to 14 years from discrete administrative areas since 2006 were identified. Each site-time period was matched to a model estimated community-based age-corrected parasite prevalence to provide predictions of prevalence in childhood (PfPR2-10). Admission with all-cause malaria, severe malaria anaemia (SMA), respiratory distress (RD) and cerebral malaria (CM) were analysed as means and predicted probabilities from Bayesian generalised mixed models. RESULTS: 52,684 malaria admissions aged 1 month to 14 years were described at 21 hospitals from 49 site-time locations where PfPR2-10 varied from < 1 to 48.7%. Twelve site-time periods were described as low transmission (PfPR2-10 < 5%), five low-moderate transmission (PfPR2-10 5-9%), 20 moderate transmission (PfPR2-10 10-29%) and 12 high transmission (PfPR2-10 ≥ 30%). The majority of malaria admissions were below 5 years of age (69-85%) and rare among children aged 10-14 years (0.7-5.4%) across all transmission settings. The mean age of all-cause malaria hospitalisation was 49.5 months (95% CI 45.1, 55.4) under low transmission compared with 34.1 months (95% CI 30.4, 38.3) at high transmission, with similar trends for each severe malaria phenotype. CM presented among older children at a mean of 48.7 months compared with 39.0 months and 33.7 months for SMA and RD, respectively. In moderate and high transmission settings, 34% and 42% of the children were aged between 2 and 23 months and so within the age range targeted by chemoprevention or vaccines. CONCLUSIONS: Targeting chemoprevention or vaccination programmes to areas where community-based parasite prevalence is ≥10% is likely to match the age ranges covered by interventions (e.g. intermittent presumptive treatment in infancy to children aged 2-23 months and current vaccine age eligibility and duration of efficacy) and the age ranges of highest disease burden.

Real world external validation of metabolic gestational age assessment in Kenya.

Using data from Ontario Canada, we previously developed machine learning-based algorithms incorporating newborn screening metabolites to estimate gestational age (GA). The objective of this study was to evaluate the use of these algorithms in a population of infants born in Siaya county, Kenya. Cord and heel prick samples were collected from newborns in Kenya and metabolic analysis was carried out by Newborn Screening Ontario in Ottawa, Canada. Postnatal GA estimation models were developed with data from Ontario with multivariable linear regression using ELASTIC NET regularization. Model performance was evaluated by applying the models to the data collected from Kenya and comparing model-derived estimates of GA to reference estimates from early pregnancy ultrasound. Heel prick samples were collected from 1,039 newborns from Kenya. Of these, 8.9% were born preterm and 8.5% were small for GA. Cord blood samples were also collected from 1,012 newborns. In data from heel prick samples, our best-performing model estimated GA within 9.5 days overall of reference GA [mean absolute error (MAE) 1.35 (95% CI 1.27, 1.43)]. In preterm infants and those small for GA, MAE was 2.62 (2.28, 2.99) and 1.81 (1.57, 2.07) weeks, respectively. In data from cord blood, model accuracy slightly decreased overall (MAE 1.44 (95% CI 1.36, 1.53)). Accuracy was not impacted by maternal HIV status and improved when the dating ultrasound occurred between 9 and 13 weeks of gestation, in both heel prick and cord blood data (overall MAE 1.04 (95% CI 0.87, 1.22) and 1.08 (95% CI 0.90, 1.27), respectively). The accuracy of metabolic model based GA estimates in the Kenya cohort was lower compared to our previously published validation studies, however inconsistency in the timing of reference dating ultrasounds appears to have been a contributing factor to diminished model performance.

The Impact of Maternal Human Immunodeficiency Virus Infection on the Burden of Respiratory Syncytial Virus Among Pregnant Women and Their Infants, Western Kenya.

BACKGROUND: Respiratory syncytial virus (RSV) is an important cause of respiratory illness worldwide; however, burden data on mother-infant pairs remain sparse in sub-Saharan Africa, where human immunodeficiency virus (HIV) is prevalent. We evaluated the impact of maternal HIV infection on the burden of RSV among mothers and their infants in western Kenya. METHODS: We enrolled pregnant women (≤20 weeks' gestation) and followed them and their newborns weekly for up to 3-6 months postpartum, to document cases of acute respiratory illness (ARI). Nasal/oropharyngeal swabs were collected and tested for RSV using polymerase chain reaction. Analyses were stratified by maternal HIV status and incidence was computed per 1000 person-months. RESULTS: Compared to RSV-negative ARI cases, RSV-positive cases were associated with cough, apnea, and hospitalization among infants. RSV incidence per 1000 person-months among mothers was 4.0 (95% confidence interval [CI], 3.2-4.4), and was twice that among the HIV-infected mothers (8.4 [95% CI, 5.7-12.0]) compared to the HIV-uninfected mothers (3.1 [95% CI, 2.3-4.0]). Among infants, incidence per 1000 person-months was 15.4 (95% CI, 12.5-18.8); incidence did not differ by HIV exposure or prematurity. CONCLUSIONS: HIV infection may increase the risk of RSV illness among pregnant women. Future maternal RSV vaccines may have added benefit in areas with high HIV prevalence.

Malaria infection and severe disease risks in Africa.

The relationship between community prevalence of Plasmodium falciparum and the burden of severe, life-threatening disease remains poorly defined. To examine the three most common severe malaria phenotypes from catchment populations across East Africa, we assembled a dataset of 6506 hospital admissions for malaria in children aged 3 months to 9 years from 2006 to 2020. Admissions were paired with data from community parasite infection surveys. A Bayesian procedure was used to calibrate uncertainties in exposure (parasite prevalence) and outcomes (severe malaria phenotypes). Each 25% increase in prevalence conferred a doubling of severe malaria admission rates. Severe malaria remains a burden predominantly among young children (3 to 59 months) across a wide range of community prevalence typical of East Africa. This study offers a quantitative framework for linking malaria parasite prevalence and severe disease outcomes in children.

SARS-CoV-2 Infection among Pregnant and Postpartum Women, Kenya, 2020-2021.

We determined incidence of severe acute respiratory syndrome coronavirus 2 and influenza virus infections among pregnant and postpartum women and their infants in Kenya during 2020-2021. Incidence of severe acute respiratory syndrome coronavirus 2 was highest among pregnant women, followed by postpartum women and infants. No influenza virus infections were identified.

Respiratory syncytial virus seasonality in three epidemiological zones of Kenya.

Understanding respiratory syncytial virus (RSV) circulation patterns is necessary to guide the timing of limited-duration interventions such as vaccines. We describe RSV circulation over multiple seasons in three distinct counties of Kenya during 2006-2018. Kilifi and Siaya counties each had consistent but distinct RSV seasonality, lasting on average 18-22 weeks. Based on data from available years, RSV did not have a clear pattern of circulation in Nairobi. This information can help guide the timing of vaccines and immunoprophylaxis products that are under development.