The Lancet Regional Health - Western Pacific

Against accelerating global urbanization, we analyzed regional cancer health disparities in Japan using nationwide cancer incidence and mortality data. This cross-sectional ecological study included 1889 Japanese municipalities, categorized as urban, suburban, and rural. Using 2015 Census data, we estimated the normalized Areal Deprivation Index (normADI) and, using 2016-2018 cancer registry and vital statistics data, estimated standardized incidence and mortality ratios with a fully Bayesian hierarchical spatial model (FBSIR/FBSMR). We examined their association by urbanicity, analyzing 3,056,535 incident cases and 1,140,250 deaths. Higher normADI was associated with increased FBSMR for all cancers, particularly in urban areas (risk ratio 1.18 for males; 1.12 for females). Mortality of stomach, colorectal, lung, and liver cancers increased with increasing deprivation in urban areas, with stronger effects for male colorectal, liver, and lung cancers as urbanicity increased. Sensitivity analyses using alternative modeling formulations, both spatial and non-spatial, yielded broadly similar results. The greater impact of ADI on cancer mortality in urban areas underscores the need for poverty-focused cancer prevention strategies with growing urban populations.

Social and mental stressors associated with the COVID-19 pandemic may promote long-term effects on child development. However, reports aimed at identifying the relationship between pandemics and child health are limited. We conducted a retrospective study to evaluate the severe acute respiratory syndrome (SARS) pandemic in 2003 and its relationship to child development indicators using a representative sample across China. Our study involved longitudinal measurements of 14,647 children, 36% of whom (n = 5216) were born before or during the SARS pandemic. Cox models were utilized to examine the effects of SARS on preterm birth and four milestones of development: age to (1) walk independently, (2) say a complete sentence, (3) count from 0 to 10, and (4) undress him/herself for urination. Mixed effect models were utilized to associate SARS with birthweight, body weight and height. Our results show that experiencing SARS during early childhood was significantly associated with delayed milestones, with adjusted hazard ratios of 3.17 [95% confidence intervals (CI): 2.71, 3.70], 3.98 (3.50, 4.53), 4.96 (4.48, 5.49), or 5.57 (5.00, 6.20) for walking independently, saying a complete sentence, counting from 0 to 10, and undressing him/herself for urination, respectively. Experiencing SARS was also associated with reduced body weight. This effect was strongest for preschool children [a weight reduction of 4.86 (0.36, 9.35) kg, 5.48 (-0.56, 11.53) kg or 5.09 (-2.12, 12.30) kg for 2, 3, 4 year-olds, respectively]. We did not identify a significant effect of maternal SARS exposure on birthweight or gestational length. Collectively, our results showed that the SARS pandemic was associated with delayed child development and provided epidemiological evidence to support the association between infectious disease epidemics and impaired child health. These results provide a useful framework to investigate and mitigate relevant impacts from the COVID-19 pandemic.

Initial cases of COVID-19 reported in Hong Kong were mostly imported from China. However, most cases reported in February 2020 were locally-acquired infections, indicating local community transmissions. We extracted the demographic, clinical and epidemiological data from 50 COVID-19 patients, who accounted for 53.8% of the cases in Hong Kong by February 2020. Whole-genome sequencing of the SARS-CoV-2 were conducted to determine the phylogenetic relatedness and transmission dynamics. Only three (6.0%) patients required ICU admission. Phylogenetic analysis identified six transmission clusters. All locally-acquired cases harboured a common mutation Orf3a G251V and were clustered in two subclades in global phylogeny of SARS-CoV-2. The estimated time to the most recent common ancestor of local COVID-2019 outbreak was December 24, 2019 with an evolutionary rate of 3.04x10-3 substitutions per site per year. The reproduction number value was 1.84. Social distancing and vigilant epidemiological control are crucial to the containment of COVID-19 transmission. Article summary linesA combined epidemiological and phylogenetic analysis of early COVID-19 outbreak in Hong Kong revealed that a SARS-CoV-2 variant with ORF3a G251V mutation accounted for all locally acquired cases, and that asymptomatic carriers could be a huge public health risk for COVID-19 control.

Socioeconomic inequalities in the double burden of child malnutrition threatens global nutrition targets 2025, especially in Eastern and Southern Africa. We aimed to quantify these inequalities from nationally representative household surveys in 13 Eastern and Southern African countries between 2000 and 2018. 13 of the latest Demographic and Health Surveys including 72,231 children under five year olds were studied. Prevalence of stunting, wasting and overweight (including obesity) were disagregated by wealth quintiles, maternal education categories and urban-rural residence for visual inspection of inequalities, and the slope index of inequality (SII) and the relative index of inequality (RII) were estimated for each country. Country-specific estimates were pooled using random-effects meta-analyses. Regional stunting and wasting prevalence was higher among children living in the poorest households, with mothers with the lowest educational level and in rural areas. In contrast, regional overweight (including obesity) prevalence was higher among children living in the richest households, with mothers with the highest educational level and urban areas. Tackling social inequalities in the distribution of the double burden of malnutrition among children in the Eastern and Southern African region will require strategies that address the reasons socially disadvantaged children become more exposed to stunting or wasting.

BackgroundHong Kong, has operated under a zero-Covid policy in the past few years. As a result, population immunity from natural infections has been low. The fifth wave in Hong Kong, caused by the Omicron variant, grew substantially in February 2022 during the transition from winter into spring. The daily number of reported cases began to decline quickly in a few days after social distancing regulations were tightened and rapid antigen test (RAT) kits were largely distributed. How the non-pharmaceutical interventions (NPIs) and seasonal factors (temperature and relative humidity) could affect the spread of Omicron remains unknown. MethodsWe developed a model with stratified immunity, to incorporate antibody responses, together with changes in mobility and seasonal factors. After taking into account the detection rates of PCR test and RAT, we fitted the model to the daily number of reported cases between 1 February and 31 March, and quantified the associated effects of individual NPIs and seasonal factors on infection dynamics. FindingsAlthough NPIs and vaccine boosters were critical in reducing the number of infections, temperature was associated with a larger change in transmissibility. Cold days appeared to drive Re from about 2-3 sharply to 10.6 (95%CI: 9.9-11.4). But this number reduced quickly below one a week later when the temperature got warmer. The model projected that if weather in March maintained as Februarys average level, the estimated cumulative incidence could increase double to about 80% of total population. InterpretationTemperature should be taken into account when making public health decisions (e.g. a more relaxed (or tightened) social distancing during a warmer (or colder) season).

In light of the rapid growth of COVID-19 in mainland China, countries and regions outside of China have implemented travel restrictions of varying intensity. Using surveillance data of symptomatic travellers arriving from mainland China and detected in Singapore, this provides a proxy on the COVID-19 in mainland China. Furthermore, this allows us to ensure that travel-related restrictions commensurate with the current epidemiological situation and risk.

Klebsiella pneumoniae infections in young infants are an escalating threat in low- and middle-income countries, yet robust longitudinal data integrating hospital burden, clinical outcomes, antimicrobial, and genomics remains scarce. We performed an 18-year (2004-2021) prospective, multicenter genomic epidemiology study across four hospitals in Bangladesh. Among 122,353 enrolled children from whom blood or cerebrospinal fluid cultures were performed, 1,600 (1.3%) yielded culture-confirmed Klebsiella pneumoniae species complex (KpSC) isolates. Positivity increased from 16 per 1,000 cases tested in 2004 to 37 per 1,000 in 2021. Hospital case-fatality rate (CFR) rose from 21.4% to 51.4% during the study, paralleling the emergence and expansion of carbapenem resistance, first detected in 2008 and reaching 81% of isolates by 2021. Neonates accounted for 80.5% of infections and experienced a CFR of 40.8%. Whole-genome sequencing of 599 representative isolates revealed four KpSC species, 145 sequence types and 92 capsular alleles. Global high-risk clones ST11, ST16 and ST147 harbouring NDM-type carbapenemases dominated recent cases. These findings document the increasing resistance and mortality associated with KpSC infections amongst neonates in Bangladesh, underscoring the urgent need for strengthened infection prevention & control, equitable access to effective combination therapies, and vaccine-based preventative strategies.

Because of the fading immunity to COVID-19 and continuous evolution of the SARS-CoV-2 Omicron variants, the next epidemic wave of COVID-19 is inevitable. The Omicron variant has been the cause of several waves of the COVID-19 epidemics in the majority of countries. Thus, lessons from other countries may provide guidance regarding the timing and magnitude of the next COVID-19 wave of the pandemic in China. In this study, the COVID-19 surveillance data from 189 countries that experienced two or more waves of the SARS-CoV-2 Omicron variant were analysed. The median peak timing between the first and second/third waves of the SARS-CoV-2 Omicron variant was 164/243 days. The peaks of the second and third waves were much lower than that of the first wave. The median relative peaks of the second and third compared with the first waves were 14.5% and 11.2%, respectively. The time window between the peak timings of the first and second waves showed no significant rank correlation with the five socioeconomic factors included in this study. However, the relative peak of the second wave increased significantly with gross domestic product per capita (P<0.001), urbanisation rate (P=0.003), population density (P=0.007), and proportion of older adults >65 years (P<0.001), although decreased significantly with the proportion of 0-14 teenagers (P<0.001). In summary, the historical situations and progression of COVID-19 outbreaks in other countries may inform the risk assessment of incoming outbreaks in mainland China; however, the timing and magnitude of the next COVID-19 wave may also be influenced by several unknown factors, including rapid viral evaluation of SARS-CoV-2

Type 2 diabetes (T2D) often exhibits long-standing disparities across populations. Spatial regression models can identify areas of epidemiological conformity and transitions between local neighborhoods to inform timely, localized public health interventions. We identified areal-level distributions of T2D rates across Malaysia and synthesized prediction models to estimate local effects and interactions of different neighborhood covariates affecting local T2D burden. We obtained aggregated counts of national level T2D cases data by administrative-districts between 2016-2020 and computed district-wise crude rates to correlate with district-level neighborhood demographic, socio-economic, safety, fitness, access to built-environments, and urban growth indicators from various national sources and census data. We applied simultaneous spatial autoregressive (SAR) models coupled with two-way interaction analyses to account for spatial autocorrelation and estimate risk factors for district-level T2D rates in Malaysia. The variation in spatial lag estimates of T2D rates by districts was influenced by the proportion of households living below 50% of the median income ({beta} = 0.009, p = 0.002) and national poverty line ({beta} = - 0.012, p = 0.001), income inequalities ({beta} = - 2.005, p = 0.004), CCTV coverage per 1000 population ({beta} = 0.070, p = 0.023), average property crime index per 1000 population ({beta} = 0.014, p = 0.033), access to bowling centers ({beta} = - 0.003, p = 0.019), and parks ({beta} = 0.007, p = 0.001). Areal-level district-wise crude T2D rate estimates were influenced by neighborhood socio-economic vulnerabilities, neighborhood safety, and neighborhood access to fitness facilities, after accounting for residual spatial correlation via SAR models.

Individual-level studies on the coronavirus disease 2019 (COVID-19) have proliferated; however, research on neighborhood-level factors associated with COVID-19 is limited. We gathered the geographic data of all publically released COVID-19 cases in China and used a case-control (1:4 ratio) design to investigate the association between having COVID-19 cases in a neighborhood and number and types of public facilities nearby. Having more restaurants, shopping centers, hotels, living facilities, recreational facilities, public transits, educational institutions, and health service facilities was associated with significantly higher odds of having COVID-19 cases in a neighborhood. The associations for restaurants, hotels, reactional and education facilities were more pronounced in cities with fewer than six million people than those in larger cities. Our results have implications for designing targeted prevention strategies at the neighborhood level to reduce the burden of COVID-19.

BackgroundThe recent Omicron-related waves of the COVID-19 pandemic have resulted in unprecedented levels of population transmission due to the variants high level of infectiousness across most of the world. China, the last large country to end its "zero-COVID" policies, is currently facing its own massive Omicron-related wave, and the final impact of that wave remains uncertain. We have seen repeatedly that the epidemiological characteristics of new variants can have profound impacts on global health outcomes. While the characteristics of these new variants are difficult to predict ahead of their emergence, considering the impact of potential future scenarios is of central importance for prudent planning and policy making. This paper samples across a range of potential variant-level characteristics to provide global forecasts of infections, hospitalisations, and deaths in the face of ongoing Omicron-related transmission and waning levels of past immunity and evaluates a range of interventions that may diminish the impact of future waves. MethodsWe created a susceptible-exposed-infectious dynamic model that accounts for vaccine uptake and effectiveness, antiviral administration, the emergence of new variants, and waning protection from both infection- and vaccine-derived immunity. Using this model, we first estimated past infections, hospitalisations, and deaths by variant, location, and day. We used these findings to more fully understand the global progression of the COVID-19 pandemic through December 12, 2022. Second, we forecasted these same outcome measures under five potential variant emergence scenarios. Third, we evaluated three different interventions in isolation and in concert within each potential variant scenario, to assess the impact of available intervention strategies through June 30, 2023. FindingsWe estimated that from November 15, 2021, through December 12, 2022, there were 8.60 billion (95% uncertainty interval [UI] 6.37-11.7) SARS-CoV-2 infections, 13.1 million (10.6-16.5) hospitalisations, and 3.04 million (2.65-3.55) deaths, the majority of which were attributable to Omicron variants (98.5% [97.4-99.1] of infections, 82.6% [76.7-86.3] of hospitalisations, and 72.4% [66.4-76.0] of deaths). Compared to the pre-Omicron pandemic period from January 1, 2020, to November 15, 2021, we estimated that there were more than twice as many infections (214% [163-286]) globally from November 15, 2021, to December 12, 2022, but only 20.6% (19.8-21.4) of the estimated deaths. The massive Omicron waves and high vaccination rates in many high-income countries have together contributed to high levels of immunity against SARS-CoV-2 infection, leaving only 97.3% (96.3-98.2) of the global population with no protection as of December 1, 2022. Concurrently, however, China, where only 17.6% [5.28-34.8] of the population have ever experienced infection due to its zero-COVID policy, requires special attention over the next few months, as all our future scenarios predict substantial increases in transmission, hospitalisation, and death in China in now that zero-COVID policies have been relaxed. Under the future scenario we consider most plausible (a scenario with another new Omicron-like variant emerging and reference levels of the drivers of transmission), we estimated there will be an additional 5.19 billion (3.11-7.78) infections, 13.6 million (8.50-21.8) hospitalisations, and 2.74 million (1.40-5.68) deaths between December 12, 2022, and June 30, 2023, with the Western Pacific region projected to sustain the highest rates of additional deaths, driven primarily by the uncontained outbreak in China. By comparison, a baseline scenario in which no new variant emerges results in 3.54 billion (2.24-5.43) infections, 6.26 million (4.11-9.65) hospitalisations, and 1.58 million (0.829-3.95) deaths in the same forecast period. The ability for a new variant to break through past infection- and vaccine-derived immunity greatly influences future outcomes: we estimate a new variant with the high severity of Delta, but correspondingly moderate immunity breakthrough rates will have difficulty overtaking current variants and will result in similar outcomes to the Omicron-like variant scenario with 3.64 billion (2.26-5.83) new infections, 7.87 million (4.81-13.0) new hospitalisations, and 2.87 million (1.03-5.56) new deaths. Finally, if we consider a variant that combines the high infectiousness and breakthrough rates of Omicron with the high severity of Delta, we again estimate 5.19 billion (3.11-7.78) new infections, but due to the presumed increase in severe outcomes, we estimate 30.2 million (13.4-51.2) new hospitalisations and 15.9 million (4.31-35.9) deaths over the forecasted period. The impacts of interventions vary by variant characteristics and region of the world, with increased mask usage and reimplementation of some mandates having massive impact in some regions while having less impact in others. Finally, assuming variant spread was as rapid as observed for Omicron, we find almost no impact of a rapidly developed and deployed variant-targeted booster. InterpretationAs infection-derived and vaccine-conferred protection wanes, we expect infections to rise, but as most of the worlds population has some level of immunity to SARS-CoV-2 as of December 12, 2022, all but the most pessimistic forecasts in this analysis do not predict a massive global surge by June 30, 2023. Paradoxically, China, due to its lower levels of population immunity and effective vaccination will likely experience substantial numbers of infections and deaths that, due to its large population size, will adversely affect the global toll. This could be substantially mitigated by existing intervention options including masking, vaccination, health-care preparedness, and effective antiviral compounds for those at most at risk of poor outcomes. While still resulting in morbidity and mortality, this endemic transmission provides protection from less transmissible variants and particularly protects against sub-lineages of the more severe pre-Omicron variants. In the scenarios where a new variant does emerge and spread globally, however, the speed of this spread may be too fast to rely on even the most quickly developed mRNA vaccines to provide protection soon enough. Existing vaccines and boosters have played an important role in increasing immunity worldwide, but the continued contribution of mask usage (both past and future) in the prevention of infection and death cannot be understated. The characteristics of future COVID-19 variants are inherently difficult to predict, and our forecasts do show considerable differences in outcomes as a function of these variant properties. Given the uncertainty surrounding what type of variant will next emerge, the world would be wise to remain vigilant in 2023 as we move to the next phase of the COVID-19 pandemic. FundingBill & Melinda Gates Foundation, J. Stanton, T. Gillespie, and J. and E. Nordstrom. Research in contextO_ST_ABSEvidence before this studyC_ST_ABSSince the beginning of the COVID-19 pandemic, there have been a plethora of COVID-19 models developed; most were designed to focus on a specific location (or small set of locations) and a short time horizon (usually less than a month). A number of modelling consortiums were created to develop ensemble predictions across models of this sort (e.g., the COVID-19 Forecast Hub [maintained by the Reich Lab of the University of Massachusetts Amherst in collaboration with USA CDC (Centers for Disease Control)] or the European COVID-19 Forecast Hub [created by a multitude of infectious disease modelling teams and coordinated by ECDC (European Centre for Disease Prevention and Control)]), and the final results typically predicted four weeks, and at most, six weeks forward. The models combined for these ensembles ran the spectrum from transmission dynamic models that incorporated complex mixing patterns between individuals, to machine learning models that were agnostic of the fact that the input and output were associated with infectious diseases. Moreover, most of these models were designed to predict the most likely outcome as opposed to evaluate potential future scenarios. A small subset of these models were created with this sort of flexibility, though they have primarily been applied to limited global regions (e.g., USA CDC scenarios) and they typically do not evaluate multiple potential scenarios three to six months into the future. The Institute for Health Metrics and Evaluation (IHME) COVID-19 model has been generating and publishing forecasts of SARS-CoV-2 infections and COVID-19 deaths globally with four-month time horizons and making these available at mostly weekly intervals on its website since March 26, 2020 (https://covid19.healthdata.org). The cadence has now slowed to monthly updates as in many parts of the world, data needed to support the modelling of COVID-19 have reduced and/or ceased to be collected as the attention of policy makers and funders is drawn elsewhere. Several epidemiological scenarios have been evaluated in these online estimates, but the outcomes have not been formally compared across these scenarios globally into 2023. This article is also the first full formal documentation of the IHME-SEI model incorporating foundation work on infection-fatality ratio, more robust cumulative infection calculations, as well as more recently developed work that allows for waning immunity. Added value of this studyTo our knowledge, this study is the first to forecast multiple future COVID-19 scenarios of variant emergence against a background of high rates of past SARS-CoV-2 exposure globally, nationally, and for a set of subnational locations, six months into the future. It is also one of the first to forecast the impact of China relaxing its zero-COVID policy. The scenarios considered were selected to represent a range of realistic potential futures and are directly comparable by region, country, and territory (and in many instances subnational units), to identify future risk as well as inform on the effectiveness of potential intervention strategies. In particular, we directly compared scenarios where a future variant is presumed to be similar to Omicron (high infectiousness, low severity, high immune-breakthrough), Delta (moderate infectiousness, high severity, moderate immune-breakthrough), a Delta with increased immune escape (moderate infectiousness, high severity, high immune-breakthrough), or the worst of both (high infectiousness, high severity, high immune-breakthrough) to a scenario where no new variant emerges. We then evaluated several interventions against each potential variant future, each in isolation and in concert. In addition to providing timely predictions for China as they remove restrictions, we provide insight into which locations may be at highest risk for future COVID-19 infections, hospitalisations, and deaths, and what they might do to mitigate the worst possible outcomes. Implications of all the available evidenceThe Omicron waves have already resulted in an estimated 8.60 billion (95% uncertainty interval [UI] 6.37-11.7) infections in the past 13 months globally (from November 15, 2021, through December 12, 2022). Previous exposure to other variants and vaccination have together resulted in 97.3% (96.3-98.2) of the global population being estimated to have some immunity to SARS-CoV-2 as of December 12, 2022. While infection- and vaccine-derived immunity has and will continue to wane, this protection and ongoing transmission of currently circulating variants will mitigate the scale of the next COVID-19 wave. The scale of mitigation possible is highly dependent on the characteristics of the next variant. To assess the potential for a COVID-19 surge in early 2023, we evaluated several future variant scenarios, as well as the unlikely baseline scenario of no new variant emerging. In the absence of any new variant, our baseline model predicts 1.58 million (0.829-3.95) deaths globally between December 12, 2022, and June 30, 2023. If a variant with similar characteristics to Omicron (eg, high infectiousness and low severity) emerges on January 15, 2023, our model predicts 2.74 million (1.40-5.68) additional deaths over the same period. A variant with the characteristics of Delta is predicted to have difficulty overtaking current variants and past immunity, and despite its substantial severity, our model predicts a number of deaths similar to an Omicron-like new variant (2.87 million [1.03-5.56]). In the worst-case scenario considered, a variant with the transmission and breakthrough characteristics of Omicron and the severity of Delta would result in 15.9 million (4.31-35.9) deaths, 14.3 million (3.33-32.7) more than a scenario where no new variant emerges. In China, the potential morbidity and mortality in 2023 is high, due to a combination of pandemic history and policy that has kept levels of population immunity to COVID-19 low. In our "worst case" variant scenario, we estimate initiatives to return mask use to 80% of the population (or the location-specific current level, if higher) as well as the reimplementation of moderate mandates would avert 32.8% (18.7-51.3) of the predicted deaths, with maximal impact occurring in the European region (44.8% [28.7-61.6]). In every variant scenario, given the estimated speed of global spread, we predict that variant-targeted mRNA boosters are not able to be deployed soon enough to have a substantial impact. While there is considerable uncertainty in the future of COVID-19 variant characteristics, this study demonstrates a range of plausible outcomes expected across a spectrum of future realities. Although it would require nations to react quickly to newly detected threats, our predictions show that increased mask use and (where necessary) reimplementation of moderate social distancing mandates can mitigate much of any future challenge.

Before January 22, 2020, only one pediatric case of COVID-19 was reported in mainland China1,2. However, a retrospective surveillance study3 identified six children who had been hospitalized for COVID-19 in one of three central Wuhan hospitals between January 7th and January 15th. Given that Wuhan has over 395 other hospitals, there may have been far more severe pediatric cases than reported.

The coronavirus disease 2019 (COVID-19) pandemic and the measures taken by authorities to control its spread had altered human behavior and mobility patterns in an unprecedented way. However, it remains unclear whether the population response to a COVID-19 outbreak varies within a city or among demographic groups. Here we utilized passively recorded cellular signaling data at a spatial resolution of 1km x 1km for over 5 million users and epidemiological surveillance data collected during the SARS-CoV-2 Omicron BA.2 outbreak from February to June 2022 in Shanghai, China, to investigate the heterogeneous response of different segments of the population at the within-city level and examine its relationship with the actual risk of infection. Changes in behavior were spatially heterogenous within the city and population groups, and associated with both the infection incidence and adopted interventions. We also found that males and individuals aged 30-59 years old traveled more frequently, traveled longer distances, and their communities were more connected; the same groups were also associated with the highest SARS-CoV-2 incidence. Our results highlight the heterogeneous behavioral change of the Shanghai population to the SARS-CoV-2 Omicron BA.2 outbreak and the its effect on the heterogenous spread of COVID-19, both spatially and demographically. These findings could be instrumental for the design of targeted interventions for the control and mitigation of future outbreaks of COVID-19 and, more broadly, of respiratory pathogens. Significance StatementOur study utilized passively recorded cellular signaling data and epidemiological surveillance data to investigate the changes human mobility to a COVID-19 outbreak at an unprecedented within-city level and examine its relationship with the actual risk of infection. Our findings highlight the heterogeneous behavioral change of the Shanghai population to the 2022 SARS-CoV-2 Omicron BA.2 outbreak and its heterogenous effect on the SARS-CoV-2 spread, both spatially and demographically. The implications of our findings could be instrumental to inform spatially targeted interventions at the within-city scale to mitigate possible new surges of COVID-19 cases as well as fostering preparedness for future respiratory infections disease outbreaks.

Although the co-occurrence of diarrhea and malnutrition is well documented, research has largely focused on the acute management of diarrheal illness. Despite its importance, longitudinal evidence characterizing post-diarrheal recovery trajectories is sparse. We sought to characterize post-diarrheal nutritional recovery trajectories among children aged 6-35 months who were malnourished at enrollment using data from the Enterics for Global Health (EFGH) Shigella Surveillance study (2022-2024). EFGH enrolled children aged 6-35 months presenting with medically-attended diarrhea and followed them at 4 weeks and 3 months post-enrollment. This analysis included children with baseline wasting, stunting, or underweight (z-score < -2) and complete anthropometric follow-up. Latent class mixed-effects models were used to identify distinct post-diarrheal growth trajectories based on changes in anthropometric z-scores over time. Multinomial modified Poisson regression models examined associations between baseline factors and trajectory membership. Among 9,480 enrolled children, 16.5% (n=1,561) were wasted, 22.7% (n=2,155) stunted, and 21.0% (n=1,994) underweight at baseline. Wasting showed greater recovery potential (80.8%) compared with stunting (38.5%) and underweight (40.3%). Recovery was shaped by factors across multiple levels. Clinical severity markers ( prolonged diarrhea, dehydration, and hypoxemia) increased the risk of nutritional failure. Age also influenced outcomes: infants were more likely to worsen, whereas older toddlers more often experienced stagnation. Interventions including exclusive breastfeeding, oral rehydration therapy, appropriate antibiotics, and zinc supplementation, improved outcomes, while unimproved sanitation undermined recovery. These findings highlight the need for integrated strategies combining infection control, nutritional rehabilitation, and water, sanitation, and hygiene interventions tailored to the childrens developmental stage. Key MessagesO_LIPost-diarrheal nutritional recovery is highly heterogeneous, with wasting showing the greatest potential for improvement, while stunting and underweight often result in persistent growth stagnation. C_LIO_LIBaseline anthropometric deficits alone are insufficient to predict recovery, highlighting the need for dynamic monitoring and individualized management. C_LIO_LIInfants are particularly vulnerable to acute nutritional deterioration, while older toddlers frequently experience growth stagnation. C_LIO_LIModifiable protective factors including exclusive breastfeeding, ORS, zinc, and appropriate antibiotics, improved outcomes, whereas poor sanitation undermined recovery. C_LIO_LIIntegrated strategies, tailored to a childs developmental stage, combining clinical care, nutrition, and environmental interventions are critical to support sustained child growth and development. C_LI

Background: Child acute malnutrition remains persistently above emergency thresholds in Chad's Sahelian drylands, with a predictable, but rarely recognized, dry season peak linked to declining pasture and livestock productivity, reduced milk availability and heightened exposure to zoonotic infections. Humanitarian responses remain largely reactive and treatment-focused, with limited evidence on preventive strategies that address drivers embedded in local livelihood systems. We evaluated the effectiveness and return on investment (ROI) of an integrated livestock management intervention designed to prevent the dry-season peak of child acute malnutrition in pastoral and agro-pastoral communities in Chad. Methods: We conducted a cluster-randomised controlled trial in Kanem and Barh-El-Gazel provinces, Chad. Seventy-six villages were randomised (1:1) to intervention or control. Eligible households had at least one child aged 6-59 months and access to milking livestock during the dry season. The intervention (December 2024-June 2025) combined livestock feed supplementation to sustain milk production near households during the dry season, household-level zoonotic risk mitigation, and nutrition counselling. Primary outcomes were the prevalence of global acute malnutrition (GAM) and severe acute malnutrition (SAM) at the dry-season peak (May 2025), assessed in a prespecified random subsample of 52 clusters. All 76 clusters were assessed post-peak (July 2025). Analyses followed an intention-to-treat approach using mixed-effects models. A societal ROI analysis was conducted over six months with projections to 24 months. Findings: At the dry-season peak, 821 children 6-59 months from 521 households were assessed across 52 villages. GAM prevalence was 22.2% in intervention villages versus 47.4% in controls (adjusted OR 0.29 [95% CI 0.18-0.49]; p<0.001), and SAM prevalence was 4.4% versus 19.4% (adjusted OR 0.17 [0.08-0.37]; p<0.001). Intervention households had higher daily milk availability (+588 mL per household; p<0.001), and children consumed more milk (+102 mL per day; p=0.008). Odds of self-reported diarrhoeal disease and acute respiratory infection were substantially lower among children in intervention villages (aOR 0.21 [0.10-0.44] and 0.22 [0.11-0.46], respectively). Post-peak, women's dietary diversity increased (aOR 3.68 [1.90-7.13]), alongside reduced workload, lower household food insecurity and distress livestock sales, improved livestock condition, and a benefit-cost ratio of 5.40 at six months, rising to 16.40 at 24 months. Interpretation: Protecting livestock productivity and sustaining children's access to milk while reducing zoonotic exposure during the pastoral lean season effectively prevents seasonal peaks of child acute malnutrition. This integrated anticipatory action and One Health livelihood-based approach offers a scalable, dignifying, high-return lifesaving preventive model for pastoral and agro-pastoral humanitarian settings.

BackgroundSince late 2021, the highly transmissible SARS-CoV-2 Omicron variant has driven a new surge of infections across the world. We used a case-ascertained study to determine the features of household transmission of SARS-CoV-2 Omicron variant in Shanghai, China. MethodsWe collected detailed information on 323 pediatric cases and their 951 household members in April 2022 during the Omicron outbreak. All household members received consecutively intensive RT-PCR testing for SARS-CoV-2 and routine symptom monitoring within 14 days after exposure to a confirmed case. We described the characteristics of study participants and estimated the transmission parameters. Both secondary infection attack rates (SARI) and secondary clinical attack rates (SARC) among adult household contacts were computed, through which the transmission heterogeneities in infectivity and susceptibility were characterized and the vaccine effectiveness were estimated. ResultsWe estimated the mean incubation period of SARS-CoV-2 Omicron variant to be 4.6 (median: 4.4, IQR: 3.1-6.0) days and the mean serial interval to be 3.9 (median:4.0, IQR: 1.4-6.5) days. The overall SARI and SARC among adult household contacts were 77.11% (95% confidence interval [CI]: 73.58%-80.63%) and 67.03% (63.09%-70.98%). We found higher household susceptibility in females, while infectivity was not significantly different in primary cases by age, sex, vaccination status and clinical severity. The estimated VEs of full vaccination was 14.8% (95% CI: 5.8%-22.9%) against Omicron infection and 21.5% (95% CI: 10.4%-31.2%) against symptomatic disease. The booster vaccination was 18.9% (95% CI: 9.0%-27.7%) and 24.3% (95% CI: 12.3%-34.7%) effective against infection and symptomatic disease, respectively. ConclusionsWe found high household transmission during the Omicron wave in Shanghai due to asymptomatic and pre-symptomatic transmission in the context of city-wide lockdown, indicating the importance of early detection and timely isolation of SARS-CoV-2 infections and quarantine of close contacts. Marginal effectiveness of inactivated vaccines against Omicron infection poses great challenge for prevention and control of the SARS-CoV-2 Omicron variant.

BackgroundSince the initial Wuhan outbreak, China has been containing COVID-19 outbreaks through its "dynamic zero-COVID" policy. Striking a balance between sustainability and cost-benefit, China has recently begun to adjust its COVID-19 response strategies, e.g. by announcing the "20 measures" on 11 November and further the "10 measures" on 7 December 2022. Strategies for safely exiting from dynamic zero-COVID (i.e. without catastrophically overburdening health systems and/or incurring unacceptably excessive morbidity and mortality) are urgently needed. MethodsWe use simulations to assess the respective and combined effectiveness of fourth-dose heterologous boosting, large-scale antiviral treatment and public health and social measures (PHSMs) that might allow China to further adjust COVID-19 response and exit from zero-COVID safely after 7 December 2022. We also assess whether local health systems can cope with the surge of COVID-19 cases posed by reopening, given that chunyun, a 40-day period with extremely high mobility across China associated with Spring Festival, will begin on 7 January 2023. FindingsReopening against Omicron transmission should be supported by the following interventions: 1) fourth-dose heterologous boosting 30-60 days before reopening by vaccinating 4-8% of the population per week with [&ge;]85% uptake across all ages; 2) timely antiviral treatment with [&ge;]60% coverage; 3) moderate PHSMs to reduce transmissibility by 47-69%. With fourth-dose vaccination coverage of 85% and antiviral coverage of 60%, the cumulative mortality burden would be reduced by 26-35% to 448-503 per million, compared with reopening without any of these interventions. Simultaneously reopening all provinces under current PHSMs would still lead to hospitalisation demand that are 1.5-2.5 times of surge hospital capacity (2.2 per 10,000 population per day). InterpretationAlthough the surge of disease burden posed by reopening in December 2022 - January 2023 would likely overload many local health systems across the country, the combined effect of vaccination, antiviral treatment and PHSMs could substantially reduce COVID-19 morbidity and mortality as China transits from dynamic-zero to normality. Planning for such a nationwide, coordinated reopening should be an urgent priority as part of the global exit from the acute phase of the COVID-19 pandemic. FundingCOVID-19 Vaccines Evaluation Program, Chinese Center for Disease Control and Prevention; Health and Medical Research Fund, Health Bureau, The Government of the Hong Kong SAR; General Research Fund, Research Grants Council, Hong Kong Research in contextO_ST_ABSEvidence before this studyC_ST_ABSWe searched PubMed and preprint archives for articles published up to 7 December 2021, that contained information about exit strategies of zero-COVID or reopening in China after the emergence of Omicron using the terms "China", "Omicron", "B.1.1.529", "COVID-19", "SARS-CoV-2", "vaccin*", "vaccine", "antiviral", "control measures", "non-pharmaceutical intervention", "public health and social measure", "zero-COVID", "exit strategy" and "reopen*". We only found one study by Wang et al (doi: 10.1101/2022.05.07.22274792) but they assessed the feasibility of sustaining SARS-CoV-2 containment with zero-COVID strategy in China. To our knowledge, there is no discussion of exit strategies of the zero-COVID strategy or assessment of feasibility of reopening in China. Added value of this studyReopening against Omicron transmission should be supported by the following interventions: 1) fourth-dose heterologous boosting 30-60 days before reopening by vaccinating 4-8% of the population per week with [&ge;]85% uptake across all ages; 2) timely antiviral treatment with [&ge;]60% coverage; 3) moderate PHSMs to reduce transmissibility by 47-69%. With fourth-dose vaccination coverage of 85% and antiviral coverage of 60%, the cumulative mortality burden would be reduced by 26-35% to 448-503 per million, compared with reopening without any of these interventions. Simultaneously reopening all provinces under current PHSMs would still lead to hospitalisation demand that are 1.5-2.5 times of surge hospital capacity (2.2 per 10,000 population per day). Implications of all the available evidenceAlthough the surge of disease burden posed by reopening in December 2022 - January 2023 would likely overload many local health systems across the country, the combined effect of vaccination, antiviral treatment and PHSMs could substantially reduce COVID-19 morbidity and mortality as China transits from dynamic-zero to normality. Planning for such a nationwide, coordinated reopening should be an urgent priority as part of the global exit from the acute phase of the COVID-19 pandemic.

BackgroundNeonatal sepsis is a major contributor to adverse neonatal outcomes in West Africa. High quality data on risk factors for sepsis in this region is limited, yet important for surveillance, prevention and management of newborns at greatest risk. This study aimed to describe the clinical epidemiology of sepsis for health-facility born neonates in an urban West African setting. MethodsThis study comprised secondary data analyses from the Gambian cohort of the PregnAnZI-2 randomised clinical trial. Relatively healthy pregnant women and their offspring who delivered at two urban health facilities were included, with a combination of active and passive surveillance until 28 days. Neonatal sepsis was defined as suspected if clinical and laboratory (abnormal FBC or CRP) criteria were met, and confirmed if blood-culture was positive. A novel conceptual framework informed logistic regression models to identify 1) factors associated with neonatal sepsis and 2) contribution of sepsis towards neonatal mortality. ResultsA total of 6515 neonates were included. The health-facility based incidence of neonatal sepsis was 20.2 cases/1000 live births (N=131 cases), predominantly early-onset (<3 days)(15.7 cases/1000 livebirths). Confirmed sepsis accounted for 22% (29/131) of all cases, with Burkholderia cepacia and Staphylococcus aureus the most prevalent bacteria in 24% (7/29) of confirmed sepsis each. Risk factors for sepsis included low 1-minute Apgar score (aOR 13.2, 95% CI 8.40-20.73), pre-labour maternal fever (aOR 5.0, 95% CI 1.15-21.69), easily recognisable congenital malformation (aOR 3.39, 95% CI 1.55-7.38) and low-birth weight (aOR 2.85, 95% CI 1.75-4.65). 40.7% of all neonatal deaths in the cohort occurred in neonates with sepsis, with 40-fold increase in mortality compared to neonates without sepsis (OR: 39.98, 95% CI 22.5 - 71.1). ConclusionSepsis, especially early onset, is a major morbidity for health facility born neonates delivered following relatively healthy pregnancy in urban Gambia, with high associated mortality. We identify neonatal phenotypes (low birth weight, newborns with low 1-minute apgar scores, or those with easily recognisable congenital malformations) who may benefit from enhanced postnatal surveillance or antibiotics to prevent or treat neonatal sepsis and reduce neonatal mortality. Trial RegistrationNCT03199547: Clinicaltrials.gov. Registered on 23rd June 2017

BackgroundGlobal under-5 mortality has declined by approximately 60% since 1990, driven largely by reductions in communicable, maternal, neonatal, and nutritional (CMNN) diseases. Yet the degree to which genetic disorders now impede further progress toward Sustainable Development Goal (SDG) 3.2 remains poorly quantified. No prior study has assessed the aggregate burden of genetically determined conditions as a unified category across the full spectrum of countries and development levels. MethodsUsing data from the Global Burden of Disease (GBD) Study 2021, we defined a composite "Total Genetic Burden" by aggregating 16 genetically determined causes of death, encompassing congenital birth defects, hemoglobinopathies, cystic fibrosis proxies, and spinal muscular atrophy proxies, across 204 countries and territories from 1990 to 2021. Age-standardized mortality rates (ASMR), proportional mortality ratios (PMR), years of life lost (YLLs), and 95% uncertainty intervals (UIs) were calculated. Temporal trends were assessed to evaluate the shifting burden over the study period. Age-specific mortality density was computed to identify periods of peak vulnerability. Deterministic frontier analysis (log-transformed quadratic quantile regression at the 5th percentile) was applied to quantify potentially avoidable mortality relative to best-observed global performance at each level of socioeconomic development. ResultsThe age-standardized mortality rate of genetic disorders in children under 5 declined from 1990 to 2021; however, the proportional mortality ratio nearly doubled (from 5.76% to 10.76%), and genetic disorders rose from the fifth to the third leading cause of under-5 death. This shift was most pronounced in high Socio-demographic Index (SDI) countries, where genetic disorders accounted for over 40% of all under-5 deaths in some nations (e.g., Libya, 46.32%). An "Epidemiological Paradox" emerged: absolute mortality correlated negatively with SDI (R = -0.79, P < 0.001), whereas proportional mortality correlated positively (R = 0.80, P < 0.001). Age-specific analysis revealed a "Neonatal Stronghold," with genetic disorders accounting for 57% of combined genetic-versus-infectious deaths in the first week of life but only 8% in children aged 1-4 years. Frontier analysis identified substantial efficiency gaps across all SDI quintiles; China and Japan sat on the effective frontier, while Afghanistan, Nigeria, and even the United States exhibited considerable potentially avoidable mortality. ConclusionsGenetic disorders have shifted from a secondary concern to a leading structural barrier to further reductions in child mortality. Achieving SDG 3.2 will require broadening global child health priorities beyond infection control to include prenatal screening, newborn screening programs, and pediatric surgical capacity building, particularly in low- and middle-income countries.

BackgroundWhile the incidence of inflammatory bowel disease (IBD) has stabilized in Western countries since 1990, it is experiencing an upward trend in newly industrializing countries. The Asian region encompasses a multitude of developing countries at varying stages of IBD progression. Therefore, comprehending the current epidemiological characteristics of the disease in this region becomes imperative, enabling countries and locales in Asia to proactively address the evolving IBD burden in the upcoming several decades. MethodsWe analyze variation trends in the burden of IBD in Asia from 1990 to 2019, employing data and methods from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD), and provide projections for future changes in IBD incidence in Asia over the next 20 years. ResultsIn 2019, the number of incidence cases of IBD in Asia was 145,561 (95% UI 124,960-170,895), the total number of prevalence cases reached nearly 2 million (95% UI 1.71-2.32), and 13,957 (95% UI 11,898-16,021) patients died of IBD. Meanwhile, the total years lived with disability (YLDs) attributed to IBD amounted to 299,663 (95% UI 198,365-418,635), while the total disability-adjusted life-years (DALYs) rose to 649,760 (95% UI 530,395-783,181). The total number of incidence cases in Asia is projected to reach 179,756 in 2040, with an age-standardized incidence rate of 2.92 per 100,000 population. ConclusionsThe increase in the overall burden of IBD in Asia is primarily driven by population growth and aging, with both incidence and DALYs continuing to rise in most countries. It is imperative for each country to adapt its measures to local conditions, improve prevailing healthcare service patterns, and draw insights from the frontier countries to respond to the evolving epidemic characteristics of IBD.