Search

Current knowledge of dengue virus (DENV) transmission provides only a partial understanding of a complex and dynamic system yielding a public health track record that has more failures than successes. An important part of the problem is that the foundation for contemporary interventions includes a series of longstanding, but untested, assumptions based on a relatively small portion of the human population; i.e., people who are convenient to study because they manifest clinically apparent disease. Approaching dengue from the perspective of people with overt illness has produced an extensive body of useful literature. It has not, however, fully embraced heterogeneities in virus transmission dynamics that are increasingly recognized as key information still missing in the struggle to control the most important insect-transmitted viral infection of humans. Only in the last 20 years have there been significant efforts to carry out comprehensive longitudinal dengue studies. This manuscript provides the rationale and comprehensive, integrated description of the methodology for a five-year longitudinal cohort study based in the tropical city of Iquitos, in the heart of the Peruvian Amazon. Primary data collection for this study was completed in 2019. Although some manuscripts have been published to date, our principal objective here is to support subsequent publications by describing in detail the structure, methodology, and significance of a specific research program. Our project was designed to study people across the entire continuum of disease, with the ultimate goal of quantifying heterogeneities in human variables that affect DENV transmission dynamics and prevention. Because our study design is applicable to other Aedes transmitted viruses, we used it to gain insights into Zika virus (ZIKV) transmission when during the project period ZIKV was introduced and circulated in Iquitos. Our prospective contact cluster investigation design was initiated by detecttion of a person with a symptomatic DENV infection and then followed that person’s immediate contacts. This allowed us to monitor individuals at high risk of DENV infection, including people with clinically inapparent and mild infections that are otherwise difficult to detect. We aimed to fill knowledge gaps by defining the contribution to DENV transmission dynamics of (1) the understudied majority of DENV-infected people with inapparent and mild infections and (2) epidemiological, entomological, and socio-behavioral sources of heterogeneity. By accounting for factors underlying variation in each person’s contribution to transmission we sought to better determine the type and extent of effort needed to better prevent virus transmission and disease.

Background:: Childhood immunisation services have been disrupted by the COVID-19 pandemic. WHO recommends considering outbreak risk using epidemiological criteria when deciding whether to conduct preventive vaccination campaigns during the pandemic. Methods:: We used two to three models per infection to estimate the health impact of 50% reduced routine vaccination coverage in 2020 and delay of campaign vaccination from 2020 to 2021 for measles vaccination in Bangladesh, Chad, Ethiopia, Kenya, Nigeria, and South Sudan, for meningococcal A vaccination in Burkina Faso, Chad, Niger, and Nigeria, and for yellow fever vaccination in the Democratic Republic of Congo, Ghana, and Nigeria. Our counterfactual comparative scenario was sustaining immunisation services at coverage projections made prior to COVID-19 (i.e. without any disruption). Results:: Reduced routine vaccination coverage in 2020 without catch-up vaccination may lead to an increase in measles and yellow fever disease burden in the modelled countries. Delaying planned campaigns in Ethiopia and Nigeria by a year may significantly increase the risk of measles outbreaks (both countries did complete their supplementary immunisation activities (SIAs) planned for 2020). For yellow fever vaccination, delay in campaigns leads to a potential disease burden rise of >1 death per 100,000 people per year until the campaigns are implemented. For meningococcal A vaccination, short-term disruptions in 2020 are unlikely to have a significant impact due to the persistence of direct and indirect benefits from past introductory campaigns of the 1- to 29-year-old population, bolstered by inclusion of the vaccine into the routine immunisation schedule accompanied by further catch-up campaigns. Conclusions:: The impact of COVID-19-related disruption to vaccination programs varies between infections and countries. Planning and implementation of campaigns should consider country and infection-specific epidemiological factors and local immunity gaps worsened by the COVID-19 pandemic when prioritising vaccines and strategies for catch-up vaccination. Funding:: Bill and Melinda Gates Foundation and Gavi, the Vaccine Alliance.

Additional file 1: Table S1. Overview of data references. Table S2. Sizes of single reactive vaccination campaigns targeting the general population or healthcare workers (HCWs). SI Text. Sensitivity analysis and extended model limitations. Fig. S1. Spillover and reactive vaccination patterns for Lassa fever virus (LASV). Fig. S2. Spillover and reactive vaccination patterns for Middle Eastern respiratory virus (MERS-CoV). Fig. S3. Spillover and reactive vaccination patterns for Nipah virus (NiV). Fig. S4. Spillover and reactive vaccination patterns for Rift Valley fever virus (RVFV). Fig. S5. Vaccine regimens required for Lassa fever virus (LASV). Fig. S6. Vaccine regimens required for Middle Eastern respiratory virus (MERS-CoV). Fig. S7. Vaccine regimens required for Nipah virus (NiV). Fig. S8. Vaccine regimens required for Rift Valley fever virus (RVFV). Fig. S9. Vaccine regimens required to vaccinate healthcare workers for Lassa fever virus (LASV). Fig. S10. Vaccine regimens required to vaccinate healthcare workers for Middle Eastern respiratory virus (MERS-CoV). Fig. S11. Vaccine regimens required to vaccinate healthcare workers for Nipah virus (NiV). Fig. S12. Vaccine regimens required to vaccinate veterinarians for Rift Valley fever virus (RVFV). Fig. S13. Vaccination impact sensitivity analysis for LASV. Fig. S14. Vaccination impact sensitivity analysis for NiV. Fig. S15. Vaccination impact sensitivity analysis for RVFV. Fig. S16. Number of cases under different R0 assumptions. Fig. S17. Number of vaccine regimens required under different R0 assumptions. Fig. S18. Number of vaccine regimens required for healthcare workers (HCWs) under different R0 assumptions. Fig. S19. Number of cases averted by vaccinating the general population under different R0 assumptions. Fig. S20. Fraction of cases averted by vaccinating the general population under different R0 assumptions. Fig. S21. Number of cases averted per vaccine regimen administered to the general population under different R0 assumptions. Fig. S22. Number of cases averted per vaccine regimen administered to healthcare workers (HCWs) under different R0 assumptions. Fig. S23. Spillover and reactive vaccination patterns for Lassa fever virus (LASV) within adm1 catchment areas. Fig. S24. Spillover and reactive vaccination patterns for Middle Eastern respiratory virus (MERS-CoV) within adm1 catchment areas. Fig. S25. Spillover and reactive vaccination patterns for Nipah virus (NiV) within adm1 catchment areas. Fig. S26. Spillover and reactive vaccination patterns for Rift Valley fever virus (RVFV) within adm1 catchment areas. Fig. S27. Spillover and reactive vaccination patterns for Lassa fever virus (LASV) within adm1 hospital catchment areas. Fig. S28. Spillover and reactive vaccination patterns for Middle Eastern respiratory virus (MERS-CoV) within adm1 hospital catchment areas. Fig. S29. Spillover and reactive vaccination patterns for Nipah virus (NiV) within adm1 hospital catchment areas. Fig. S30. Spillover and reactive vaccination patterns for Rift Valley fever virus (RVFV) within adm1 hospital catchment areas. Fig. S31. Geographic distribution of spillover cases and reactive vaccination campaigns for adm1 catchment areas. Fig. S32. Geographic distribution of spillover cases and reactive vaccination campaigns for adm1 hospital catchment areas. Fig. S33. Annual cases and reactive vaccination impacts for adm1 catchment areas. Fig. S34. Annual cases and reactive vaccination impacts for adm1 hospital-based catchment areas.

Additional file 1. Additional figures and tables.

[This corrects the article DOI: 10.1371/journal.pntd.0009603.].

The global population at risk from mosquito-borne diseases-including dengue, yellow fever, chikungunya and Zika-is expanding in concert with changes in the distribution of two key vectors: Aedes aegypti and Aedes albopictus. The distribution of these species is largely driven by both human movement and the presence of suitable climate. Using statistical mapping techniques, we show that human movement patterns explain the spread of both species in Europe and the United States following their introduction. We find that the spread of Ae. aegypti is characterized by long distance importations, while Ae. albopictus has expanded more along the fringes of its distribution. We describe these processes and predict the future distributions of both species in response to accelerating urbanization, connectivity and climate change. Global surveillance and control efforts that aim to mitigate the spread of chikungunya, dengue, yellow fever and Zika viruses must consider the so far unabated spread of these mosquitos. Our maps and predictions offer an opportunity to strategically target surveillance and control programmes and thereby augment efforts to reduce arbovirus burden in human populations globally.

Background: Major gains have been made in reducing malaria transmission in many parts of the world, principally by scaling-up coverage with long-lasting insecticidal nets and indoor residual spraying. Historically, choice of vector control intervention has been largely guided by a parameter sensitivity analysis of George Macdonald's theory of vectorial capacity that suggested prioritizing methods that kill adult mosquitoes. While this advice has been highly successful for transmission suppression, there is a need to revisit these arguments as policymakers in certain areas consider which combinations of interventions are required to eliminate malaria.Methods and Results: Using analytical solutions to updated equations for vectorial capacity we build on previous work to show that, while adult killing methods can be highly effective under many circumstances, other vector control methods are frequently required to fill effective coverage gaps. These can arise due to pre-existing or developing mosquito physiological and behavioral refractoriness but also due to additive changes in the relative importance of different vector species for transmission. Furthermore, the optimal combination of interventions will depend on the operational constraints and costs associated with reaching high coverage levels with each intervention.Conclusions: Reaching specific policy goals, such as elimination, in defined contexts requires increasingly non-generic advice from modelling. Our results emphasize the importance of measuring baseline epidemiology, intervention coverage, vector ecology and program operational constraints in predicting expected outcomes with different combinations of interventions.

Most host-parasite systems exhibit remarkable heterogeneity in the contribution to transmission of certain individuals, locations, host infectious states, or parasite strains. While significant advancements have been made in the understanding of the impact of transmission heterogeneity in epidemic dynamics and parasite persistence and evolution, the knowledge base of the factors contributing to transmission heterogeneity is limited. We argue that research efforts should move beyond considering the impact of single sources of heterogeneity and account for complex couplings between conditions with potential synergistic impacts on parasite transmission. Using theoretical approaches and empirical evidence from various host-parasite systems, we investigate the ecological and epidemiological significance of couplings between heterogeneities and discuss their potential role in transmission dynamics and the impact of control.

On November 18, 2016, the WHO ended its designation of the Zika virus (ZIKV) epidemic as a Public Health Emergency of International Concern (PHEIC). At the same time, ZIKV transmission continues in Asia, with the number of Asian countries reporting Zika cases increasing over the last 2 years. Applying a method that combines epidemiological theory with data on epidemic size and drivers of transmission, we characterised the population at risk of ZIKV infection from Aedes aegypti mosquitoes in 15 countries in Asia. Projections made under the assumption of no pre-existing immunity suggest that up to 785 (range: 730–992) million people in Asia would be at risk of ZIKV infection under that scenario. Assuming that 20% of ZIKV infections are symptomatic, this implies an upper limit of 146–198 million for the population at risk of a clinical episode of Zika. Due to limited information about pre-existing immunity to ZIKV in the region, we were unable to make specific numerical projections under a more realistic assumption about pre-existing immunity. Even so, combining numerical projections under an assumption of no pre-existing immunity together with theoretical insights about the extent to which pre-existing immunity may lower epidemic size, our results suggest that the population at risk of ZIKV infection in Asia could be even larger than in the Americas. As a result, we conclude that the WHO’s removal of the PHEIC designation should not be interpreted as an indication that the threat posed by ZIKV has subsided.

Mosquito-borne diseases pose some of the greatest challenges in public health, especially in tropical and sub-tropical regions of theworld. Efforts to control these diseases have been underpinned by a theoretical framework developed for malaria by Ross and Macdonald, including models, metrics for measuring transmission, and theory of control that identifies key vulnerabilities in the transmission cycle. That framework, especially Macdonald's formula for R0 and its entomological derivative, vectorial capacity, are nowused to study dynamics and design interventions for many mosquito-borne diseases. A systematic review of 388 models published between 1970 and 2010 found that the vast majority adopted the Ross-Macdonald assumption of homogeneous transmission in a well-mixed population. Studies comparing models and data question these assumptions and point to the capacity to model heterogeneous, focal transmission as the most important but relatively unexplored component in current theory. Fine-scale heterogeneity causes transmission dynamics to be nonlinear, and poses problems for modeling, epidemiology and measurement. Novel mathematical approaches show how heterogeneity arises from the biology and the landscape on which the processes of mosquito biting and pathogen transmission unfold. Emerging theory focuses attention on the ecological and social context formosquito blood feeding, themovement of both hosts and mosquitoes, and the relevant spatial scales for measuring transmission and for modeling dynamics and control., Transactions of the Royal Society of Tropical Medicine and Hygiene, 108(4), pp.185-197; 2014

Background The serial interval is a fundamentally important quantity in infectious disease epidemiology that has numerous applications to inferring patterns of transmission from case data. Many of these applications are apropos of efforts to eliminate falciparum malaria from locations throughout the world, yet the serial interval for this disease is poorly understood quantitatively. Methods To obtain a quantitative estimate of the serial interval for falciparum malaria, the sum of the components of the falciparum malaria transmission cycle was taken based on a combination of mathematical models and empirical data. During this process, a number of factors were identified that account for substantial variability in the serial interval across different contexts. Results Treatment with anti-malarial drugs roughly halves the serial interval due to an abbreviated period of human infectiousness, seasonality results in different serial intervals at different points in the transmission season, and variability in within-host dynamics results in many individuals whose serial intervals do not follow average behaviour. Furthermore, 24.5 % of secondary cases presenting clinically did so prior to the primary cases being identified through active detection of infection. Conclusions These results have important implications for epidemiological applications that rely on quantitative estimates of the serial interval of falciparum malaria and other diseases characterized by prolonged infections and complex ecological drivers.

Background:Vaccination is one of the most effective public health interventions. We investigate the impact of vaccination activities for Haemophilus influenzae type b, hepatitis B, human papillomavirus, Japanese encephalitis, measles, Neisseria meningitidis serogroup A, rotavirus, rubella, Streptococcus pneumoniae, and yellow fever over the years 2000–2030 across 112 countries.Methods:Twenty-one mathematical models estimated disease burden using standardised demographic and immunisation data. Impact was attributed to the year of vaccination through vaccine-activity-stratified impact ratios.Results:We estimate 97 (95%CrI[80, 120]) million deaths would be averted due to vaccination activities over 2000–2030, with 50 (95%CrI[41, 62]) million deaths averted by activities between 2000 and 2019. For children under-5 born between 2000 and 2030, we estimate 52 (95%CrI[41, 69]) million more deaths would occur over their lifetimes without vaccination against these diseases.Conclusions:This study represents the largest assessment of vaccine impact before COVID-19-related disruptions and provides motivation for sustaining and improving global vaccination coverage in the future.Funding:VIMC is jointly funded by Gavi, the Vaccine Alliance, and the Bill and Melinda Gates Foundation (BMGF) (BMGF grant number: OPP1157270 / INV-009125). Funding from Gavi is channelled via VIMC to the Consortium’s modelling groups (VIMC-funded institutions represented in this paper: Imperial College London, London School of Hygiene and Tropical Medicine, Oxford University Clinical Research Unit, Public Health England, Johns Hopkins University, The Pennsylvania State University, Center for Disease Analysis Foundation, Kaiser Permanente Washington, University of Cambridge, University of Notre Dame, Harvard University, Conservatoire National des Arts et Métiers, Emory University, National University of Singapore). Funding from BMGF was used for salaries of the Consortium secretariat (authors represented here: TBH, MJ, XL, SE-L, JT, KW, NMF, KAMG); and channelled via VIMC for travel and subsistence costs of all Consortium members (all authors). We also acknowledge funding from the UK Medical Research Council and Department for International Development, which supported aspects of VIMC's work (MRC grant number: MR/R015600/1).JHH acknowledges funding from National Science Foundation Graduate Research Fellowship; Richard and Peggy Notebaert Premier Fellowship from the University of Notre Dame. BAL acknowledges funding from NIH/NIGMS (grant number R01 GM124280) and NIH/NIAID (grant number R01 AI112970). The Lives Saved Tool (LiST) receives funding support from the Bill and Melinda Gates Foundation.This paper was compiled by all coauthors, including two coauthors from Gavi. Other funders had no role in study design, data collection, data analysis, data interpretation, or writing of the report. All authors had full access to all the data in the study and had final responsibility for the decision to submit for publication.

Summary Background Childhood immunisation services have been disrupted by the COVID-19 pandemic. WHO recommends considering outbreak risk using epidemiological criteria when deciding whether to conduct preventive vaccination campaigns during the pandemic. Methods We used 2-3 models per infection to estimate the health impact of 50% reduced routine vaccination coverage in 2020 and delay of campaign vaccination from 2020 to 2021 for measles vaccination in Bangladesh, Chad, Ethiopia, Kenya, Nigeria, and South Sudan, for meningococcal A vaccination in Burkina Faso, Chad, Niger, and Nigeria, and for yellow fever vaccination in the Democratic Republic of Congo, Ghana, and Nigeria. Our counterfactual comparative scenario was sustaining immunisation services at coverage projections made prior to COVID-19 (i.e. without any disruption). Findings Reduced routine vaccination coverage in 2020 without catch-up vaccination may lead to an increase in measles and yellow fever disease burden in the modelled countries. Delaying planned campaigns in Ethiopia and Nigeria by a year may significantly increased the risk of measles outbreaks (both countries did complete their SIAS planned for 2020). For yellow fever vaccination, delay in campaigns leads to a potential disease burden rise of >1 death per 100,000 people until the campaigns are implemented. For meningococcal A vaccination, short term disruptions in 2020 are unlikely to have a significant impact due to the persistence of direct and indirect benefits from past introductory campaigns of the 1 to 29-year-old population, bolstered by inclusion of the vaccine into the routine immunisation schedule accompanied by further catch-up campaigns. Interpretation The impact of COVID-19-related disruption to vaccination programs varies between infections and countries. Planning and implementation of campaigns should consider country and infection-specific epidemiological factors and local immunity gaps worsened by the COVID-19 pandemic when prioritising vaccines and strategies for catch-up vaccination. Funding Bill & Melinda Gates Foundation and Gavi, the Vaccine Alliance Research in context Evidence before the study We searched PubMed for (COVID-19 OR coronavirus OR SARS-CoV-2) AND (child health intervention OR vaccin* or immuni*) AND (disruption OR suspension OR reduction) AND (indirect effect OR health impact) on January 14, 2021, with no language restrictions. We found 178 articles of which 13 articles were relevant. Six articles reported some empirical data on immunization disruption in Bangladesh, Japan, Kenya, Nigeria, Pakistan, Saudi Arabia, South Africa, Spain and Italy, and a survey study focussed on immunization disruption in low and middle-income countries. One article proposed using the WHO health systems framework to assess the effects of COVID-19 on immunisation programmes in South Africa, another study on leveraging systems thinking and implementation science to improve immunization system performance in Africa, and two studies were review articles. One modelling study focused on the indirect effects, including reduction in routine immunisation services, of the COVID-19 pandemic on maternal and child mortality in low-income and middle-income countries. Another modelling study focused on a benefit-risk analysis of routine childhood immunisation during the COVID-19 pandemic in Africa. We also found one other study in the grey literature that analysed the impact on SARS-CoV-2 infections as a result of fixed-post and door-to-door vaccination campaigns targeted at children under five years of age in an Ethiopia-like setting. Added value of this study We estimated the increase in cases and deaths caused by the disruption to immunisation services leading to outbreaks for measles, meningococcal A and yellow fever in 10 countries. The reduction in routine immunisation coverage among under-immunised cohorts of children has enhanced the risk of outbreaks which cannot be averted without catch-up vaccination. This can lead to an increase of 9.89% (0.91 additional deaths per 100,000 individuals, or 48,000 in total) across the three diseases from 2020 to 2030 in the countries considered. Results vary by infection and country, but generally most excess deaths are due to measles. Postponing campaign immunisation may not have a detrimental short-term health impact if campaign immunisation is implemented ahead of future outbreaks caused by these immunity gaps. Implications of the available evidence The COVID-19 pandemic has caused significant disruptions to routine services and vaccination campaigns and resulted in immunity gaps with potential to cause outbreaks in the affected populations. The short-term and long-term health impact differ between measles, meningococcal A and yellow fever vaccination and by countries based on the local epidemiological situation. Thereby, catch-up vaccination should be planned by considering the heterogeneity in population susceptibility across different countries to measles, meningococcal A and yellow fever outbreaks and implemented in time to prevent these outbreaks. The study findings can inform risk-benefit trade-off discussions around the timing of campaigns.