Alarming Trends in Dengue Incidence and Mortality in Bangladesh.

Bangladesh is currently experiencing the country's largest and deadliest dengue outbreak on record. This year's outbreak has been characterized by an early seasonal surge in cases, rapid geographic spread, and a high fatality rate. The alarming trends in dengue incidence and mortality this year is an urgent wake-up call for public health policymakers and researchers to pay closer attention to dengue dynamics in South Asia, to strengthen the surveillance system and diagnostic capabilities, and to develop tools and methods for guiding strategic resource allocation and control efforts.

Quantifying the impact of SARS-CoV-2 temporal vaccination trends and disparities on disease control.

SARS-CoV-2 vaccines have been distributed at unprecedented speed. Still, little is known about temporal vaccination trends, their association with socioeconomic inequality, and their consequences for disease control. Using data from 161 countries/territories and 58 states, we examined vaccination rates across high and low socioeconomic status (SES), showing that disparities in coverage exist at national and subnational levels. We also identified two distinct vaccination trends: a rapid initial rollout, quickly reaching a plateau, or sigmoidal and slow to begin. Informed by these patterns, we implemented an SES-stratified mechanistic model, finding profound differences in mortality and incidence across these two vaccination types. Timing of initial rollout affects disease outcomes more substantially than final coverage or degree of SES disparity. Unexpectedly, timing is not associated with wealth inequality or GDP per capita. While socioeconomic disparity should be addressed, accelerating initial rollout for all over focusing on increasing coverage is an accessible intervention that could minimize the burden of disease across socioeconomic groups.

The impact of current and future climates on spatiotemporal dynamics of influenza in a tropical setting.

Although the drivers of influenza have been well studied in high-income settings in temperate regions, many open questions remain about the burden, seasonality, and drivers of influenza dynamics in the tropics. In temperate climates, the inverse relationship between specific humidity and transmission can explain much of the observed temporal and spatial patterns of influenza outbreaks. Yet, this relationship fails to explain seasonality, or lack there-of, in tropical and subtropical countries. Here, we analyzed eight years of influenza surveillance data from 12 locations in Bangladesh to quantify the role of climate in driving disease dynamics in a tropical setting with a distinct rainy season. We find strong evidence for a nonlinear bimodal relationship between specific humidity and influenza transmission in Bangladesh, with highest transmission occurring for relatively low and high specific humidity values. We simulated influenza burden under current and future climate in Bangladesh using a mathematical model with a bimodal relationship between humidity and transmission, and decreased transmission at very high temperatures, while accounting for changes in population immunity. The climate-driven mechanistic model can accurately capture both the temporal and spatial variation in influenza activity observed across Bangladesh, highlighting the usefulness of mechanistic models for low-income countries with inadequate surveillance. By using climate model projections, we also highlight the potential impact of climate change on influenza dynamics in the tropics and the public health consequences.

Longitudinal Analysis of SARS-CoV-2 Vaccine Breakthrough Infections Reveals Limited Infectious Virus Shedding and Restricted Tissue Distribution.

Background: The global effort to vaccinate people against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) during an ongoing pandemic has raised questions about how vaccine breakthrough infections compare with infections in immunologically naive individuals and the potential for vaccinated individuals to transmit the virus. Methods: We examined viral dynamics and infectious virus shedding through daily longitudinal sampling in 23 adults infected with SARS-CoV-2 at varying stages of vaccination, including 6 fully vaccinated individuals. Results: The durations of both infectious virus shedding and symptoms were significantly reduced in vaccinated individuals compared with unvaccinated individuals. We also observed that breakthrough infections are associated with strong tissue compartmentalization and are only detectable in saliva in some cases. Conclusions: Vaccination shortens the duration of time of high transmission potential, minimizes symptom duration, and may restrict tissue dissemination.

Daily longitudinal sampling of SARS-CoV-2 infection reveals substantial heterogeneity in infectiousness.

The dynamics of SARS-CoV-2 replication and shedding in humans remain poorly understood. We captured the dynamics of infectious virus and viral RNA shedding during acute infection through daily longitudinal sampling of 60 individuals for up to 14 days. By fitting mechanistic models, we directly estimated viral expansion and clearance rates and overall infectiousness for each individual. Significant person-to-person variation in infectious virus shedding suggests that individual-level heterogeneity in viral dynamics contributes to 'superspreading'. Viral genome loads often peaked days earlier in saliva than in nasal swabs, indicating strong tissue compartmentalization and suggesting that saliva may serve as a superior sampling site for early detection of infection. Viral loads and clearance kinetics of Alpha (B.1.1.7) and previously circulating non-variant-of-concern viruses were mostly indistinguishable, indicating that the enhanced transmissibility of this variant cannot be explained simply by higher viral loads or delayed clearance. These results provide a high-resolution portrait of SARS-CoV-2 infection dynamics and implicate individual-level heterogeneity in infectiousness in superspreading.

Longitudinal analysis of SARS-CoV-2 vaccine breakthrough infections reveal limited infectious virus shedding and restricted tissue distribution.

The global effort to vaccinate people against SARS-CoV-2 in the midst of an ongoing pandemic has raised questions about the nature of vaccine breakthrough infections and the potential for vaccinated individuals to transmit the virus. These questions have become even more urgent as new variants of concern with enhanced transmissibility, such as Delta, continue to emerge. To shed light on how vaccine breakthrough infections compare with infections in immunologically naive individuals, we examined viral dynamics and infectious virus shedding through daily longitudinal sampling in a small cohort of adults infected with SARS-CoV-2 at varying stages of vaccination. The durations of both infectious virus shedding and symptoms were significantly reduced in vaccinated individuals compared with unvaccinated individuals. We also observed that breakthrough infections are associated with strong tissue compartmentalization and are only detectable in saliva in some cases. These data indicate that vaccination shortens the duration of time of high transmission potential, minimizes symptom duration, and may restrict tissue dissemination.

Daily sampling of early SARS-CoV-2 infection reveals substantial heterogeneity in infectiousness.

The dynamics of SARS-CoV-2 replication and shedding in humans remain poorly understood. We captured the dynamics of infectious virus and viral RNA shedding during acute infection through daily longitudinal sampling of 60 individuals for up to 14 days. By fitting mechanistic models, we directly estimate viral reproduction and clearance rates, and overall infectiousness for each individual. Significant person-to-person variation in infectious virus shedding suggests that individual-level heterogeneity in viral dynamics contributes to superspreading. Viral genome load often peaked days earlier in saliva than in nasal swabs, indicating strong compartmentalization and suggesting that saliva may serve as a superior sampling site for early detection of infection. Viral loads and clearance kinetics of B.1.1.7 and non-B.1.1.7 viruses in nasal swabs were indistinguishable, however B.1.1.7 exhibited a significantly slower pre-peak growth rate in saliva. These results provide a high-resolution portrait of SARS-CoV-2 infection dynamics and implicate individual-level heterogeneity in infectiousness in superspreading.

Longitudinal Assessment of Diagnostic Test Performance Over the Course of Acute SARS-CoV-2 Infection.

BACKGROUND: Serial screening is critical for restricting spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) by facilitating timely identification of infected individuals to interrupt transmission. Variation in sensitivity of different diagnostic tests at different stages of infection has not been well documented. METHODS: In a longitudinal study of 43 adults newly infected with SARS-CoV-2, all provided daily saliva and nasal swabs for quantitative reverse transcription polymerase chain reaction (RT-qPCR), Quidel SARS Sofia antigen fluorescent immunoassay (FIA), and live virus culture. RESULTS: Both RT-qPCR and Quidel SARS Sofia antigen FIA peaked in sensitivity during the period in which live virus was detected in nasal swabs, but sensitivity of RT-qPCR tests rose more rapidly prior to this period. We also found that serial testing multiple times per week increases the sensitivity of antigen tests. CONCLUSIONS: RT-qPCR tests are more effective than antigen tests at identifying infected individuals prior to or early during the infectious period and thus for minimizing forward transmission (given timely results reporting). All tests showed >98% sensitivity for identifying infected individuals if used at least every 3 days. Daily screening using antigen tests can achieve approximately 90% sensitivity for identifying infected individuals while they are viral culture positive.

Longitudinal assessment of diagnostic test performance over the course of acute SARS-CoV-2 infection.

WHAT IS ALREADY KNOWN ABOUT THIS TOPIC?: Diagnostic tests and sample types for SARS-CoV-2 vary in sensitivity across the infection period. WHAT IS ADDED BY THIS REPORT?: We show that both RTqPCR (from nasal swab and saliva) and the Quidel SARS Sofia FIA rapid antigen tests peak in sensitivity during the period in which live virus can be detected in nasal swabs, but that the sensitivity of RTqPCR tests rises more rapidly in the pre-infectious period. We also use empirical data to estimate the sensitivities of RTqPCR and antigen tests as a function of testing frequency. WHAT ARE THE IMPLICATIONS FOR PUBLIC HEALTH PRACTICE?: RTqPCR tests will be more effective than rapid antigen tests at identifying infected individuals prior to or early during the infectious period and thus for minimizing forward transmission (provided results reporting is timely). All modalities, including rapid antigen tests, showed >94% sensitivity to detect infection if used at least twice per week. Regular surveillance/screening using rapid antigen tests 2-3 times per week can be an effective strategy to achieve high sensitivity (>95%) for identifying infected individuals.

Socioeconomic status determines COVID-19 incidence and related mortality in Santiago, Chile.

The COVID-19 pandemic has affected cities particularly hard. Here, we provide an in-depth characterization of disease incidence and mortality and their dependence on demographic and socioeconomic strata in Santiago, a highly segregated city and the capital of Chile. Our analyses show a strong association between socioeconomic status and both COVID-19 outcomes and public health capacity. People living in municipalities with low socioeconomic status did not reduce their mobility during lockdowns as much as those in more affluent municipalities. Testing volumes may have been insufficient early in the pandemic in those places, and both test positivity rates and testing delays were much higher. We find a strong association between socioeconomic status and mortality, measured by either COVID-19-attributed deaths or excess deaths. Finally, we show that infection fatality rates in young people are higher in low-income municipalities. Together, these results highlight the critical consequences of socioeconomic inequalities on health outcomes.

Lockdowns result in changes in human mobility which may impact the epidemiologic dynamics of SARS-CoV-2.

In response to the SARS-CoV-2 pandemic, unprecedented travel restrictions and stay-at-home orders were enacted around the world. Ultimately, the public's response to announcements of lockdowns-defined as restrictions on both local movement or long distance travel-will determine how effective these kinds of interventions are. Here, we evaluate the effects of lockdowns on human mobility and simulate how these changes may affect epidemic spread by analyzing aggregated mobility data from mobile phones. We show that in 2020 following lockdown announcements but prior to their implementation, both local and long distance movement increased in multiple locations, and urban-to-rural migration was observed around the world. To examine how these behavioral responses to lockdown policies may contribute to epidemic spread, we developed a simple agent-based spatial model. Our model shows that this increased movement has the potential to increase seeding of the epidemic in less urban areas, which could undermine the goal of the lockdown in preventing disease spread. Lockdowns play a key role in reducing contacts and controlling outbreaks, but appropriate messaging surrounding their announcement and careful evaluation of changes in mobility are needed to mitigate the possible unintended consequences.

Malaria trends in Ethiopian highlands track the 2000 'slowdown' in global warming.

A counterargument to the importance of climate change for malaria transmission has been that regions where an effect of warmer temperatures is expected, have experienced a marked decrease in seasonal epidemic size since the turn of the new century. This decline has been observed in the densely populated highlands of East Africa at the center of the earlier debate on causes of the pronounced increase in epidemic size from the 1970s to the 1990s. The turnaround of the incidence trend around 2000 is documented here with an extensive temporal record for malaria cases for both Plasmodium falciparum and Plasmodium vivax in an Ethiopian highland. With statistical analyses and a process-based transmission model, we show that this decline was driven by the transient slowdown in global warming and associated changes in climate variability, especially ENSO. Decadal changes in temperature and concurrent climate variability facilitated rather than opposed the effect of interventions.

Socioeconomic status determines COVID-19 incidence and related mortality in Santiago, Chile.

The current coronavirus disease 2019 (COVID-19) pandemic has impacted dense urban populations particularly hard. Here, we provide an in-depth characterization of disease incidence and mortality patterns, and their dependence on demographic and socioeconomic strata in Santiago, a highly segregated city and the capital of Chile. We find that among all age groups, there is a strong association between socioeconomic status and both mortality -measured either by direct COVID-19 attributed deaths or excess deaths- and public health capacity. Specifically, we show that behavioral factors like human mobility, as well as health system factors such as testing volumes, testing delays, and test positivity rates are associated with disease outcomes. These robust patterns suggest multiple possibly interacting pathways that can explain the observed disease burden and mortality differentials: (i) in lower socioeconomic status municipalities, human mobility was not reduced as much as in more affluent municipalities; (ii) testing volumes in these locations were insufficient early in the pandemic and public health interventions were applied too late to be effective; (iii) test positivity and testing delays were much higher in less affluent municipalities, indicating an impaired capacity of the health-care system to contain the spread of the epidemic; and (iv) infection fatality rates appear much higher in the lower end of the socioeconomic spectrum. Together, these findings highlight the exacerbated consequences of health-care inequalities in a large city of the developing world, and provide practical methodological approaches useful for characterizing COVID-19 burden and mortality in other segregated urban centers.

Frequency-dependent selection can forecast evolution in Streptococcus pneumoniae.

Predicting how pathogen populations will change over time is challenging. Such has been the case with Streptococcus pneumoniae, an important human pathogen, and the pneumococcal conjugate vaccines (PCVs), which target only a fraction of the strains in the population. Here, we use the frequencies of accessory genes to predict changes in the pneumococcal population after vaccination, hypothesizing that these frequencies reflect negative frequency-dependent selection (NFDS) on the gene products. We find that the standardized predicted fitness of a strain, estimated by an NFDS-based model at the time the vaccine is introduced, enables us to predict whether the strain increases or decreases in prevalence following vaccination. Further, we are able to forecast the equilibrium post-vaccine population composition and assess the invasion capacity of emerging lineages. Overall, we provide a method for predicting the impact of an intervention on pneumococcal populations with potential application to other bacterial pathogens in which NFDS is a driving force.

The Impact of Climate Change on Vaccine-Preventable Diseases: Insights From Current Research and New Directions.

PURPOSE OF REVIEW: Vaccine-preventable diseases remain a major public health concern globally. Climate is a key driver of the dynamics of many infectious diseases, including those that are vaccine preventable. Understanding the impact of climate change on vaccine-preventable diseases is, thus, an important public health research priority. Here, we summarize the recent literature and highlight promising directions for future research. RECENT FINDINGS: Vaccine-preventable enteric diseases, such as cholera, exhibit sensitivity to precipitation and flooding events. The predicted increase in extreme weather events as a result of climate change could exacerbate outbreaks of these pathogens. For airborne pathogens, temperature and specific humidity have been shown to be the most important environmental drivers, although the impact of climate change on disease burden and dynamics remains unclear. Finally, the transmission dynamics of vector-borne diseases are dependent on both temperature and precipitation, and climate change is expected to alter the burden and geographic range of these diseases. However, understanding the interacting effects of multiple factors, including socioeconomic and ecological factors, on the vector-borne disease ecosystem will be a crucial step towards forecasting disease burden under climate change. Recent work has demonstrated associations between climate and transmission of vaccine-preventable diseases. Translating these findings into forecasts under various climate change scenarios will require mechanistic frameworks that account for both intrinsic and extrinsic drivers of transmission, and the non-linear effects on disease burden. Future research should also pay greater attention to uncertainty in both the climate modeling processes as well as disease outcomes in the context of vaccine-preventable diseases.

Tube Well Use as Protection Against Rotavirus Infection During the Monsoons in an Urban Setting.

Rotavirus, a diarrheal pathogen spread via fecal-oral transmission, is typically characterized by a winter incidence peak in most countries. Unlike for cholera and other waterborne infections, the role of sanitation and socioeconomic factors on the spatial variation of rotavirus seasonality remains unclear. In the current study, we analyzed their association with rotavirus seasonality, specifically the odds of monsoon cases, across 46 locations from 2001 to 2012 in Dhaka. Drinking water from tube wells, compared to other sources, has a clear protective effect against cases during the monsoon, when flooding and water contamination are more likely. This finding supports a significant environmental component of transmission.

Cholera forecast for Dhaka, Bangladesh, with the 2015-2016 El Niño: Lessons learned.

A substantial body of work supports a teleconnection between the El Niño-Southern Oscillation (ENSO) and cholera incidence in Bangladesh. In particular, high positive anomalies during the winter (Dec-Feb) in sea surface temperatures (SST) in the tropical Pacific have been shown to exacerbate the seasonal outbreak of cholera following the monsoons from August to November. Climate studies have indicated a role of regional precipitation over Bangladesh in mediating this long-distance effect. Motivated by this previous evidence, we took advantage of the strong 2015-2016 El Niño event to evaluate the predictability of cholera dynamics for the city in recent times based on two transmission models that incorporate SST anomalies and are fitted to the earlier surveillance records starting in 1995. We implemented a mechanistic temporal model that incorporates both epidemiological processes and the effect of ENSO, as well as a previously published statistical model that resolves space at the level of districts (thanas). Prediction accuracy was evaluated with "out-of-fit" data from the same surveillance efforts (post 2008 and 2010 for the two models respectively), by comparing the total number of cholera cases observed for the season to those predicted by model simulations eight to twelve months ahead, starting in January each year. Although forecasts were accurate for the low cholera risk observed for the years preceding the 2015-2016 El Niño, the models also predicted a high probability of observing a large outbreak in fall 2016. Observed cholera cases up to Oct 2016 did not show evidence of an anomalous season. We discuss these predictions in the context of regional and local climate conditions, which show that despite positive regional rainfall anomalies, rainfall and inundation in Dhaka remained low. Possible explanations for these patterns are given together with future implications for cholera dynamics and directions to improve their prediction for the city.

Climate forcing and infectious disease transmission in urban landscapes: integrating demographic and socioeconomic heterogeneity.

Urbanization and climate change are the two major environmental challenges of the 21st century. The dramatic expansion of cities around the world creates new conditions for the spread, surveillance, and control of infectious diseases. In particular, urban growth generates pronounced spatial heterogeneity within cities, which can modulate the effect of climate factors at local spatial scales in large urban environments. Importantly, the interaction between environmental forcing and socioeconomic heterogeneity at local scales remains an open area in infectious disease dynamics, especially for urban landscapes of the developing world. A quantitative and conceptual framework on urban health with a focus on infectious diseases would benefit from integrating aspects of climate forcing, population density, and level of wealth. In this paper, we review what is known about these drivers acting independently and jointly on urban infectious diseases; we then outline elements that are missing and would contribute to building such a framework.

Differential and enhanced response to climate forcing in diarrheal disease due to rotavirus across a megacity of the developing world.

The role of climate forcing in the population dynamics of infectious diseases has typically been revealed via retrospective analyses of incidence records aggregated across space and, in particular, over whole cities. Here, we focus on the transmission dynamics of rotavirus, the main diarrheal disease in infants and young children, within the megacity of Dhaka, Bangladesh. We identify two zones, the densely urbanized core and the more rural periphery, that respond differentially to flooding. Moreover, disease seasonality differs substantially between these regions, spanning variation comparable to the variation from tropical to temperate regions. By combining process-based models with an extensive disease surveillance record, we show that the response to climate forcing is mainly seasonal in the core, where a more endemic transmission resulting from an asymptomatic reservoir facilitates the response to the monsoons. The force of infection in this monsoon peak can be an order of magnitude larger than the force of infection in the more epidemic periphery, which exhibits little or no postmonsoon outbreak in a pattern typical of nearby rural areas. A typically smaller peak during the monsoon season nevertheless shows sensitivity to interannual variability in flooding. High human density in the core is one explanation for enhanced transmission during troughs and an associated seasonal monsoon response in this diarrheal disease, which unlike cholera, has not been widely viewed as climate-sensitive. Spatial demographic, socioeconomic, and environmental heterogeneity can create reservoirs of infection and enhance the sensitivity of disease systems to climate forcing, especially in the populated cities of the developing world.