142 research outputs found
Accelerating Policy Decisions to Adopt Haemophilus influenzae Type b Vaccine: A Global, Multivariable Analysis
Jessica Shearer and colleagues analyze data from 147 countries to identify factors that influence the time taken to introduce routine vaccination against Haemophilus influenzae type b (Hib)
Neurobiological Models of Two-Choice Decision Making Can Be Reduced to a One-Dimensional Nonlinear Diffusion Equation
The response behaviors in many two-alternative choice tasks are well described by so-called sequential sampling models. In these models, the evidence for each one of the two alternatives accumulates over time until it reaches a threshold, at which point a response is made. At the neurophysiological level, single neuron data recorded while monkeys are engaged in two-alternative choice tasks are well described by winner-take-all network models in which the two choices are represented in the firing rates of separate populations of neurons. Here, we show that such nonlinear network models can generally be reduced to a one-dimensional nonlinear diffusion equation, which bears functional resemblance to standard sequential sampling models of behavior. This reduction gives the functional dependence of performance and reaction-times on external inputs in the original system, irrespective of the system details. What is more, the nonlinear diffusion equation can provide excellent fits to behavioral data from two-choice decision making tasks by varying these external inputs. This suggests that changes in behavior under various experimental conditions, e.g. changes in stimulus coherence or response deadline, are driven by internal modulation of afferent inputs to putative decision making circuits in the brain. For certain model systems one can analytically derive the nonlinear diffusion equation, thereby mapping the original system parameters onto the diffusion equation coefficients. Here, we illustrate this with three model systems including coupled rate equations and a network of spiking neurons
The Association of Systemic Microvascular Changes with Lung Function and Lung Density: A Cross-Sectional Study
10.1371/journal.pone.0050224PLoS ONE712
Sequelae due to bacterial meningitis among African children: a systematic literature review
<p>Abstract</p> <p>Background</p> <p>African children have some of the highest rates of bacterial meningitis in the world. Bacterial meningitis in Africa is associated with high case fatality and frequent neuropsychological sequelae. The objective of this study is to present a comprehensive review of data on bacterial meningitis sequelae in children from the African continent.</p> <p>Methods</p> <p>We conducted a systematic literature search to identify studies from Africa focusing on children aged between 1 month to 15 years with laboratory-confirmed bacterial meningitis. We extracted data on neuropsychological sequelae (hearing loss, vision loss, cognitive delay, speech/language disorder, behavioural problems, motor delay/impairment, and seizures) and mortality, by pathogen.</p> <p>Results</p> <p>A total of 37 articles were included in the final analysis representing 21 African countries and 6,029 children with confirmed meningitis. In these studies, nearly one fifth of bacterial meningitis survivors experienced in-hospital sequelae (median = 18%, interquartile range (IQR) = 13% to 27%). About a quarter of children surviving pneumococcal meningitis and <it>Haemophilus influenzae </it>type b (Hib) meningitis had neuropsychological sequelae by the time of hospital discharge, a risk higher than in meningococcal meningitis cases (median = 7%). The highest in-hospital case fatality ratios observed were for pneumococcal meningitis (median = 35%) and Hib meningitis (median = 25%) compared to meningococcal meningitis (median = 4%). The 10 post-discharge studies of children surviving bacterial meningitis were of varying quality. In these studies, 10% of children followed-up post discharge died (range = 0% to 18%) and a quarter of survivors had neuropsychological sequelae (range = 3% to 47%) during an average follow-up period of 3 to 60 months.</p> <p>Conclusion</p> <p>Bacterial meningitis in Africa is associated with high mortality and risk of neuropsychological sequelae. Pneumococcal and Hib meningitis kill approximately one third of affected children and cause clinically evident sequelae in a quarter of survivors prior to hospital discharge. The three leading causes of bacterial meningitis are vaccine preventable, and routine use of conjugate vaccines could provide substantial health and economic benefits through the prevention of childhood meningitis cases, deaths and disability.</p
Past, present, and future of global health financing : a review of development assistance, government, out-of-pocket, and other private spending on health for 195 countries, 1995-2050
Background Comprehensive and comparable estimates of health spending in each country are a key input for health policy and planning, and are necessary to support the achievement of national and international health goals. Previous studies have tracked past and projected future health spending until 2040 and shown that, with economic development, countries tend to spend more on health per capita, with a decreasing share of spending from development assistance and out-of-pocket sources. We aimed to characterise the past, present, and predicted future of global health spending, with an emphasis on equity in spending across countries. Methods We estimated domestic health spending for 195 countries and territories from 1995 to 2016, split into three categories-government, out-of-pocket, and prepaid private health spending-and estimated development assistance for health (DAH) from 1990 to 2018. We estimated future scenarios of health spending using an ensemble of linear mixed-effects models with time series specifications to project domestic health spending from 2017 through 2050 and DAH from 2019 through 2050. Data were extracted from a broad set of sources tracking health spending and revenue, and were standardised and converted to inflation-adjusted 2018 US dollars. Incomplete or low-quality data were modelled and uncertainty was estimated, leading to a complete data series of total, government, prepaid private, and out-of-pocket health spending, and DAH. Estimates are reported in 2018 US dollars, 2018 purchasing-power parity-adjusted dollars, and as a percentage of gross domestic product. We used demographic decomposition methods to assess a set of factors associated with changes in government health spending between 1995 and 2016 and to examine evidence to support the theory of the health financing transition. We projected two alternative future scenarios based on higher government health spending to assess the potential ability of governments to generate more resources for health. Findings Between 1995 and 2016, health spending grew at a rate of 4.00% (95% uncertainty interval 3.89-4.12) annually, although it grew slower in per capita terms (2.72% [2.61-2.84]) and increased by less than 8.0 trillion (7.8-8.1) in 2016 (comprising 8.6% [8.4-8.7] of the global economy and 5252 (5184-5319) in high-income countries, 81 (74-89) in lower-middle-income countries, and 9.5 billion, 24.3% of total DAH), although spending on other infectious diseases (excluding tuberculosis and malaria) grew fastest from 2010 to 2018 (6.27% per year). The leading sources of DAH were the USA and private philanthropy (excluding corporate donations and the Bill & Melinda Gates Foundation). For the first time, we included estimates of China's contribution to DAH ( 15.0 trillion (14.0-16.0) by 2050 (reaching 9.4% [7.6-11.3] of the global economy and $ 21.3 trillion [19.8-23.1] in purchasing-power parity-adjusted dollars), but at a lower growth rate of 1.84% (1.68-2.02) annually, and with continuing disparities in spending between countries. In 2050, we estimate that 0.6% (0.6-0.7) of health spending will occur in currently low-income countries, despite these countries comprising an estimated 15.7% of the global population by 2050. The ratio between per capita health spending in high-income and low-income countries was 130.2 (122.9-136.9) in 2016 and is projected to remain at similar levels in 2050 (125.9 [113.7-138.1]). The decomposition analysis identified governments' increased prioritisation of the health sector and economic development as the strongest factors associated with increases in government health spending globally. Future government health spending scenarios suggest that, with greater prioritisation of the health sector and increased government spending, health spending per capita could more than double, with greater impacts in countries that currently have the lowest levels of government health spending. Interpretation Financing for global health has increased steadily over the past two decades and is projected to continue increasing in the future, although at a slower pace of growth and with persistent disparities in per-capita health spending between countries. Out-of-pocket spending is projected to remain substantial outside of high-income countries. Many low-income countries are expected to remain dependent on development assistance, although with greater government spending, larger investments in health are feasible. In the absence of sustained new investments in health, increasing efficiency in health spending is essential to meet global health targets.Peer reviewe
Past, present, and future of global health financing: a review of development assistance, government, out-of-pocket, and other private spending on health for 195 countries, 1995–2050
Background: Comprehensive and comparable estimates of health spending in each country are a key input for health
policy and planning, and are necessary to support the achievement of national and international health goals. Previous
studies have tracked past and projected future health spending until 2040 and shown that, with economic development,
countries tend to spend more on health per capita, with a decreasing share of spending from development assistance
and out-of-pocket sources. We aimed to characterise the past, present, and predicted future of global health spending,
with an emphasis on equity in spending across countries.
Methods: We estimated domestic health spending for 195 countries and territories from 1995 to 2016, split into three
categories—government, out-of-pocket, and prepaid private health spending—and estimated development assistance
for health (DAH) from 1990 to 2018. We estimated future scenarios of health spending using an ensemble of linear
mixed-effects models with time series specifications to project domestic health spending from 2017 through 2050
and DAH from 2019 through 2050. Data were extracted from a broad set of sources tracking health spending and
revenue, and were standardised and converted to inflation-adjusted 2018 US dollars. Incomplete or low-quality data
were modelled and uncertainty was estimated, leading to a complete data series of total, government, prepaid private,
and out-of-pocket health spending, and DAH. Estimates are reported in 2018 US dollars, 2018 purchasing-power
parity-adjusted dollars, and as a percentage of gross domestic product. We used demographic decomposition
methods to assess a set of factors associated with changes in government health spending between 1995 and 2016
and to examine evidence to support the theory of the health financing transition. We projected two alternative future
scenarios based on higher government health spending to assess the potential ability of governments to generate
more resources for health.
Findings: Between 1995 and 2016, health spending grew at a rate of 4·00% (95% uncertainty interval 3·89–4·12)
annually, although it grew slower in per capita terms (2·72% [2·61–2·84]) and increased by less than 8·0 trillion (7·8–8·1) in 2016 (comprising 8·6% [8·4–8·7] of the global economy and 5252 (5184–5319) in high-income
countries, 81 (74–89) in lower-middle-income countries, and
9·5 billion, 24·3% of total DAH), although spending on other infectious diseases
(excluding tuberculosis and malaria) grew fastest from 2010 to 2018 (6·27% per year). The leading sources of DAH
were the USA and private philanthropy (excluding corporate donations and the Bill & Melinda Gates Foundation).
For the first time, we included estimates of China’s contribution to DAH (15·0 trillion (14·0–16·0) by 2050 (reaching 9·4% [7·6–11·3] of the global
economy and $21·3 trillion [19·8–23·1] in purchasing-power parity-adjusted dollars), but at a lower growth rate of
1·84% (1·68–2·02) annually, and with continuing disparities in spending between countries. In 2050, we estimate
that 0·6% (0·6–0·7) of health spending will occur in currently low-income countries, despite these countries
comprising an estimated 15·7% of the global population by 2050. The ratio between per capita health spending in
high-income and low-income countries was 130·2 (122·9–136·9) in 2016 and is projected to remain at similar levels
in 2050 (125·9 [113·7–138·1]). The decomposition analysis identified governments’ increased prioritisation of the
health sector and economic development as the strongest factors associated with increases in government health
spending globally. Future government health spending scenarios suggest that, with greater prioritisation of the
health sector and increased government spending, health spending per capita could more than double, with greater
impacts in countries that currently have the lowest levels of government health spending
Interpretation: Financing for global health has increased steadily over the past two decades and is projected to continue
increasing in the future, although at a slower pace of growth and with persistent disparities in per-capita health
spending between countries. Out-of-pocket spending is projected to remain substantial outside of high-income
countries. Many low-income countries are expected to remain dependent on development assistance, although with
greater government spending, larger investments in health are feasible. In the absence of sustained new investments
in health, increasing efficiency in health spending is essential to meet global health targets.
Funding: Bill & Melinda Gates Foundatio
The global distribution of lymphatic filariasis, 2000–18: a geospatial analysis
Background
Lymphatic filariasis is a neglected tropical disease that can cause permanent disability through disruption of the lymphatic system. This disease is caused by parasitic filarial worms that are transmitted by mosquitos. Mass drug administration (MDA) of antihelmintics is recommended by WHO to eliminate lymphatic filariasis as a public health problem. This study aims to produce the first geospatial estimates of the global prevalence of lymphatic filariasis infection over time, to quantify progress towards elimination, and to identify geographical variation in distribution of infection.
Methods
A global dataset of georeferenced surveyed locations was used to model annual 2000–18 lymphatic filariasis prevalence for 73 current or previously endemic countries. We applied Bayesian model-based geostatistics and time series methods to generate spatially continuous estimates of global all-age 2000–18 prevalence of lymphatic filariasis infection mapped at a resolution of 5 km2 and aggregated to estimate total number of individuals infected.
Findings
We used 14 927 datapoints to fit the geospatial models. An estimated 199 million total individuals (95% uncertainty interval 174–234 million) worldwide were infected with lymphatic filariasis in 2000, with totals for WHO regions ranging from 3·1 million (1·6–5·7 million) in the region of the Americas to 107 million (91–134 million) in the South-East Asia region. By 2018, an estimated 51 million individuals (43–63 million) were infected. Broad declines in prevalence are observed globally, but focal areas in Africa and southeast Asia remain less likely to have attained infection prevalence thresholds proposed to achieve local elimination.
Interpretation
Although the prevalence of lymphatic filariasis infection has declined since 2000, MDA is still necessary across large populations in Africa and Asia. Our mapped estimates can be used to identify areas where the probability of meeting infection thresholds is low, and when coupled with large uncertainty in the predictions, indicate additional data collection or intervention might be warranted before MDA programmes cease
Health sector spending and spending on HIV/AIDS, tuberculosis, and malaria, and development assistance for health: progress towards Sustainable Development Goal 3
Background: Sustainable Development Goal (SDG) 3 aims to “ensure healthy lives and promote well-being for all at all
ages”. While a substantial effort has been made to quantify progress towards SDG3, less research has focused on
tracking spending towards this goal. We used spending estimates to measure progress in financing the priority areas
of SDG3, examine the association between outcomes and financing, and identify where resource gains are most
needed to achieve the SDG3 indicators for which data are available.
Methods: We estimated domestic health spending, disaggregated by source (government, out-of-pocket, and prepaid
private) from 1995 to 2017 for 195 countries and territories. For disease-specific health spending, we estimated
spending for HIV/AIDS and tuberculosis for 135 low-income and middle-income countries, and malaria in
106 malaria-endemic countries, from 2000 to 2017. We also estimated development assistance for health (DAH) from
1990 to 2019, by source, disbursing development agency, recipient, and health focus area, including DAH for
pandemic preparedness. Finally, we estimated future health spending for 195 countries and territories from 2018 until
2030. We report all spending estimates in inflation-adjusted 2019 US7·9 trillion (95% uncertainty interval 7·8–8·0) in 2017 and is expected to increase to 20·2 billion
(17·0–25·0) and on tuberculosis it was 5·1 billion (4·9–5·4). Development assistance for health was 374 million of DAH was provided
for pandemic preparedness, less than 1% of DAH. Although spending has increased across HIV/AIDS, tuberculosis,
and malaria since 2015, spending has not increased in all countries, and outcomes in terms of prevalence, incidence,
and per-capita spending have been mixed. The proportion of health spending from pooled sources is expected to
increase from 81·6% (81·6–81·7) in 2015 to 83·1% (82·8–83·3) in 2030.
Interpretation: Health spending on SDG3 priority areas has increased, but not in all countries, and progress towards
meeting the SDG3 targets has been mixed and has varied by country and by target. The evidence on the scale-up of
spending and improvements in health outcomes suggest a nuanced relationship, such that increases in spending do
not always results in improvements in outcomes. Although countries will probably need more resources to achieve
SDG3, other constraints in the broader health system such as inefficient allocation of resources across interventions
and populations, weak governance systems, human resource shortages, and drug shortages, will also need to be
addressed.
Funding: The Bill & Melinda Gates Foundatio
Mapping age- and sex-specific HIV prevalence in adults in sub-Saharan Africa, 2000–2018
Background: Human immunodeficiency virus and acquired immune deficiency syndrome (HIV/AIDS) is still among the leading causes of disease burden and mortality in sub-Saharan Africa (SSA), and the world is not on track to meet targets set for ending the epidemic by the Joint United Nations Programme on HIV/AIDS (UNAIDS) and the United Nations Sustainable Development Goals (SDGs). Precise HIV burden information is critical for effective geographic and epidemiological targeting of prevention and treatment interventions. Age- and sex-specific HIV prevalence estimates are widely available at the national level, and region-wide local estimates were recently published for adults overall. We add further dimensionality to previous analyses by estimating HIV prevalence at local scales, stratified into sex-specific 5-year age groups for adults ages 15–59 years across SSA. Methods: We analyzed data from 91 seroprevalence surveys and sentinel surveillance among antenatal care clinic (ANC) attendees using model-based geostatistical methods to produce estimates of HIV prevalence across 43 countries in SSA, from years 2000 to 2018, at a 5 × 5-km resolution and presented among second administrative level (typically districts or counties) units. Results: We found substantial variation in HIV prevalence across localities, ages, and sexes that have been masked in earlier analyses. Within-country variation in prevalence in 2018 was a median 3.5 times greater across ages and sexes, compared to for all adults combined. We note large within-district prevalence differences between age groups: for men, 50% of districts displayed at least a 14-fold difference between age groups with the highest and lowest prevalence, and at least a 9-fold difference for women. Prevalence trends also varied over time; between 2000 and 2018, 70% of all districts saw a reduction in prevalence greater than five percentage points in at least one sex and age group. Meanwhile, over 30% of all districts saw at least a five percentage point prevalence increase in one or more sex and age group. Conclusions: As the HIV epidemic persists and evolves in SSA, geographic and demographic shifts in prevention and treatment efforts are necessary. These estimates offer epidemiologically informative detail to better guide more targeted interventions, vital for combating HIV in SSA. © 2022, The Author(s).Funding text 1: S Afzal acknowledges support of the Pakistan Society of Medical Infectious Diseases and King Edward Medical University to access the relevant data of HIV from various sources. T W Bärnighausen was supported by the Alexander von Humboldt Foundation through the Alexander von Humboldt Professor award, funded by the German Federal Ministry of Education and Research. F Carvalho and E Fernandes acknowledge support from Fundação para a Ciência e a Tecnologia (FCT), I.P., in the scope of the project UIDP/04378/2020 and UIDB/04378/2020 of the Research Unit on Applied Molecular Biosciences - UCIBIO and the project LA/P/0140/2020 of the Associate Laboratory Institute for Health and Bioeconomy - i4HB; FCT/MCTES (Ministério da Ciência, Tecnologia e Ensino Superior) through the project UIDB/50006/2020. K Deribe acknowledges support by the Wellcome Trust [grant number 201900/Z/16/Z] as part of his International Intermediate Fellowship. C Herteliu and A Pana are partially supported by a grant of the Romanian National Authority for Scientific Research and Innovation, CNDS-UEFISCDI, project number PN-III-P4-ID-PCCF-2016-0084. Claudiu Herteliu is partially supported by a grant of the Romanian Ministry of Research Innovation and Digitalization, MCID, project number ID-585-CTR-42-PFE-2021. Y J Kim acknowledges support by the Research Management Centre, Xiamen University Malaysia [No. XMUMRF/2020-C6/ITCM/0004]. S L Koulmane Laxminarayana acknowledges institutional support by the Manipal Academy of Higher Education. K Krishan acknowledges non-financial support from UGC Centre of Advanced Study, CAS II, Department of Anthropology, Panjab University, Chandigarh, India. M Kumar would like to acknowledge NIH/FIC K43 TW010716-04. I Landires is a member of the Sistema Nacional de Investigación (SNI), supported by the Secretaría Nacional de Ciencia, Tecnología e Innovación (SENACYT), Panama. V Nuñez-Samudio is a member of the Sistema Nacional de Investigación (SNI), which is supported by Panama’s Secretaría Nacional de Ciencia, Tecnología e Innovación (SENACYT). O O Odukoya was supported by the Fogarty International Center of the National Institutes of Health under the Award Number K43TW010704. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. Z Quazi Syed acknowledges support from JNMC, Datta Meghe Institute of Medical Sciences. A I Ribeiro was supported by National Funds through FCT, under the ‘Stimulus of Scientific Employment – Individual Support’ program within the contract CEECIND/02386/2018. A M Samy acknowledges the support from a fellowship of the Egyptian Fulbright Mission program and Ain Shams University. R Shrestha acknowledges support from NIDA K01 Award: K01DA051346. N Taveira acknowledges support from FCT and Aga Khan Development Network (AKDN) - Portugal Collaborative Research Network in Portuguese speaking countries in Africa (project reference: 332821690), and by the European & Developing Countries Clinical Trials Partnership (EDCTP), UE (project reference: RIA2016MC-1615). B Unnikrishnan acknowledges support from Kasturba Medical College, Mangalore, Manipal Academy of Higher Education, Manipal. ; Funding text 2: LBD sub-Saharan Africa HIV Prevalence Collaborators S Afzal acknowledges support of the Pakistan Society of Medical Infectious Diseases and King Edward Medical University to access the relevant data of HIV from various sources. T W Bärnighausen was supported by the Alexander von Humboldt Foundation through the Alexander von Humboldt Professor award, funded by the German Federal Ministry of Education and Research. F Carvalho and E Fernandes acknowledge support from Fundação para a Ciência e a Tecnologia (FCT), I.P., in the scope of the project UIDP/04378/2020 and UIDB/04378/2020 of the Research Unit on Applied Molecular Biosciences - UCIBIO and the project LA/P/0140/2020 of the Associate Laboratory Institute for Health and Bioeconomy - i4HB; FCT/MCTES (Ministério da Ciência, Tecnologia e Ensino Superior) through the project UIDB/50006/2020. K Deribe acknowledges support by the Wellcome Trust [grant number 201900/Z/16/Z] as part of his International Intermediate Fellowship. C Herteliu and A Pana are partially supported by a grant of the Romanian National Authority for Scientific Research and Innovation, CNDS-UEFISCDI, project number PN-III-P4-ID-PCCF-2016-0084. Claudiu Herteliu is partially supported by a grant of the Romanian Ministry of Research Innovation and Digitalization, MCID, project number ID-585-CTR-42-PFE-2021. Y J Kim acknowledges support by the Research Management Centre, Xiamen University Malaysia [No. XMUMRF/2020-C6/ITCM/0004]. S L Koulmane Laxminarayana acknowledges institutional support by the Manipal Academy of Higher Education. K Krishan acknowledges non-financial support from UGC Centre of Advanced Study, CAS II, Department of Anthropology, Panjab University, Chandigarh, India. M Kumar would like to acknowledge NIH/FIC K43 TW010716-04. I Landires is a member of the Sistema Nacional de Investigación (SNI), supported by the Secretaría Nacional de Ciencia, Tecnología e Innovación (SENACYT), Panama. V Nuñez-Samudio is a member of the Sistema Nacional de Investigación (SNI), which is supported by Panama’s Secretaría Nacional de Ciencia, Tecnología e Innovación (SENACYT). O O Odukoya was supported by the Fogarty International Center of the National Institutes of Health under the Award Number K43TW010704. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. Z Quazi Syed acknowledges support from JNMC, Datta Meghe Institute of Medical Sciences. A I Ribeiro was supported by National Funds through FCT, under the ‘Stimulus of Scientific Employment – Individual Support’ program within the contract CEECIND/02386/2018. A M Samy acknowledges the support from a fellowship of the Egyptian Fulbright Mission program and Ain Shams University. R Shrestha acknowledges support from NIDA K01 Award: K01DA051346. N Taveira acknowledges support from FCT and Aga Khan Development Network (AKDN) - Portugal Collaborative Research Network in Portuguese speaking countries in Africa (project reference: 332821690), and by the European & Developing Countries Clinical Trials Partnership (EDCTP), UE (project reference: RIA2016MC-1615). B Unnikrishnan acknowledges support from Kasturba Medical College, Mangalore, Manipal Academy of Higher Education, Manipal.; Funding text 3: This work was primarily supported by grant OPP1132415 from the Bill & Melinda Gates Foundation. The funder of the study had no role in study design, data collection, data analysis, data interpretation, writing of the report, or decision to publish. The corresponding authors had full access to all the data in the study and had final responsibility for the decision to submit for publication. ; Funding text 4: S Afzal reports leadership or fiduciary role in other board, society, committee or advocacy group, unpaid, with the Pakistan society of Community Medicine & Public Health, the Pakistan Association of Medical Editors, and the Pakistan Society of Medical Infectious Diseases, all outside the submitted work. R Ancuceanu reports 5 payment or honoraria for lectures, presentations, speakers bureaus, manuscript writing, or educational events from Avvie, Sandoz, and B Braun, all outside the submitted work. T W Bärnighausen reports research grants from the European Union (Horizon 2020 and EIT Health), German Research Foundation (DFG), US National Institutes of Health, German Ministry of Education and Research, Alexander von Humboldt Foundation, Else-Kröner-Fresenius-Foundation, Wellcome Trust, Bill & Melinda Gates Foundation, KfW, UNAIDS, and WHO; consulting fees from KfW on the OSCAR initiative in Vietnam; participation on a Data Safety Monitoring Board or Advisory Board with the NIH-funded study “Healthy Options” (PIs: Smith Fawzi, Kaaya), Chair, Data Safety and Monitoring Board (DSMB), German National Committee on the “Future of Public Health Research and Education,” Chair of the scientific advisory board to the EDCTP Evaluation, Member of the UNAIDS Evaluation Expert Advisory Committee, National Institutes of Health Study Section Member on Population and Public Health Approaches to HIV/AIDS (PPAH), US National Academies of Sciences, Engineering, and Medicine’s Committee for the “Evaluation of Human Resources for Health in the Republic of Rwanda under the President’s Emergency Plan for AIDS Relief (PEPFAR),” University of Pennsylvania (UPenn) Population Aging Research Center (PARC) External Advisory Board Member; leadership or fiduciary role in other board, society, committee or advocacy group, paid or unpaid, as co-chair of the Global Health Hub Germany (which was initiated by the German Ministry of Health); all outside the submitted work. J das Neves reports grants or contracts from Ref. 13605 – Programa GÉNESE, Gilead Portugal (PGG/002/2016 – Programa GÉNESE, Gilead Portugal) outside the submitted work. L Dwyer-Lindgren reports support for the present manuscript from the Bill & Melinda Gates Foundation through grant OPP1132415. I Filip reports other financial or non-financial interests from Avicenna Medical and Clinical Research Institute, outside the submitted work. E Haeuser reports support for the present manuscript from the Bill & Melinda Gates Foundation through grant OPP1132415. C Herteliu reports grants from Romanian Ministry of Research Innovation and Digitalization, MCID, for project number ID-585-CTR-42-PFE-2021 (Jan 2022-Jun 2023) “Enhancing institutional performance through development of infrastructure and transdisciplinary research ecosystem within socio-economic domain – PERFECTIS,” from Romanian National Authority for Scientific Research and Innovation, CNDS-UEFISCDI, for project number PN-III-P4-ID-PCCF-2016-0084 (Oct 2018-Sep 2022) “Understanding and modelling time-space patterns of psychology-related inequalities and polarization,” and project number PN-III-P2-2.1-SOL-2020-2-0351 (Jun 2020-Oct 2020) “Approaches within public health management in the context of COVID-19 pandemic,” and from the Ministry of Labour and Social Justice, Romania for project number “Agenda for skills Romania 2020-2025”; all outside the submitted work. J J Jozwiak reports payment or honoraria for lectures, presentations, speakers bureaus, manuscript writing, or educational events from Teva, Amgen, Synexus, Boehringer Ingelheim, Zentiva, and Sanofi as personal fees, all outside the submitted work. J Khubchandani reports other financial interests from Teva Pharmaceuticals, all outside the submitted work. K Krishnan reports other non-financial support from UGC Centre of Advanced Study, CAS II, Department of Anthropology, Panjab University, Chandigarh, India, outside the submitted work. H J Larson reports grants or contracts from the MacArthur Foundation and Merck to London School of Hygeine and Tropical Medicine, and from the Vaccine Confidence Fund to the University of Washington; payment or honoraria for lectures, presentations, speakers bureaus, manuscript writing, or educational events from Center for Strategic and International Studies as payment to LSHTM for co-chairing HighLevel Panel and from GSK as personal payment for developing training sessions and lectures; leadership or fiduciary role in other board, society, committee or advocacy group, pair, with the ApiJect Advisory Board; all outside the submitted work. O O Odukoya reports support for the present manuscript from the Fogarty International Center of the National Institutes of Health under the Award Number K43TW010704. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. A Pans reports grants from Romanian National Authority for Scientific Research and Innovation, CNDS-UEFISCDI, for project number PN-III-P4-ID-PCCF-2016-0084 (Oct 2018-Sep 2022) “Understanding and modelling time-space patterns of psychology-related inequalities and polarization,” and project number PN-III-P2-2.1-SOL-2020-2-0351 (Jun 2020-Oct 2020) “Approaches within public health management in the context of COVID-19 pandemic,” outside the submitted work. S R Pandi-Perumal reports royalties from Springer for editing services; stock or stock options in Somnogen Canada Inc as the President and Chief Executive Officer; all outside the submitted work. A Radfar reports other financial or non-financial interests from Avicenna Medical and Clinical Research Institute, outside the submitted work. A I Ribeiro reports grants or contracts from National Funds through FCT, under the ‘Stimulus of Scientific Employment – Individual Support’ program within the contract CEECIND/02386/2018, outside the submitted work. J M Ross reports support for the present manuscript from the Bill & Melinda Gates Foundation through grant OPP1132415; grants or contracts from National Institutes of Health and Firland Foundation as payments to their institution; consulting fees from United States Agency for International Development as personal payments, and from KNCV Tuberculosis Foundation as payments to their institution; all outside the submitted work. E Rubagotti reports payment or honoraria for lectures, presentations, speakers bureaus, manuscript writing, or educational events from the Greenwich China Office and Unviersity Prince Mohammad VI, Morocco, all outside the submitted work. B Sartorius reports grants or contracts from DHSC – GRAM Project; Leadership or fiduciary role in other board, society, committee or advocacy group, paid or unpaid, as a member of the GBD Scientific Council and a Member of WHO RGHS; all outside the submitted work. J A Singh reports consulting fees from Crealta/Horizon, Medisys, Fidia, PK Med, Two labs Inc, Adept Field Solutions, Clinical Care options, Clearview healthcare partners, Putnam associates, Focus forward, Navigant consulting, Spherix, MedIQ, Jupiter Life Science LLC, UBM LLC, Trio Health, Medscape, WebMD, and Practice Point communications, and the National Institutes of Health and the American College of Rheumatology; payment or honoraria for participating in the speakers bureau for Simply Speaking; support for attending meetings and/or travel from the steering committee of OMERACT, to attend their meeting every 2 years; participation on a Data Safety Monitoring Board or Advisory Board as an unpaid member of the FDA Arthritis Advisory Committee; leadership or fiduciary role in other board, society, committee or advocacy group, paid or unpaid, as a member of the steering committee of OMERACT, an international organization that develops measures for clinical trials and receives arm’s length funding from 12 pharmaceutical companies, with the Veterans Affairs Rheumatology Field Advisory Committee as Chair, and with the UAB Cochrane Musculoskeletal Group Satellite Center on Network Meta-analysis as a director and editor; stock or stock options in TPT Global Tech, Vaxart pharmaceuticals, Atyu Biopharma, Adaptimmune Therapeutics, GeoVax Labs, Pieris Pharmaceuticals, Enzolytics Inc, Series Therapeutics, Tonix Pharmaceuticals, and Charlotte’s Web Holdings Inc. and previously owned stock options in Amarin, Viking, and Moderna pharmaceuticals; all outside the submitted work. N Taveira reports grants or contracts from FCT and Aga Khan Development Network (AKDN) – Portugal Collaborative Research Network in Portuguese speaking countries in Africa (Project reference: 332821690) and from European & Developing Countries Clinical Trials Partnership (EDCTP), UE (Project reference: RIA2016MC-1615), as payments made to their institution, all outside the submitted work
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