Teresa Yamana

Columbia University | CU · Department of Environmental Health Sciences

The impact of climate change on malaria transmission has been hotly debated. Recent conclusions have been drawn using relatively simple biological models and statistical approaches with inconsistent predictions. Consequently, the Intergovernmental Panel on Climate Change Fifth Assessment Report (IPCC AR5) echoes this uncertainty, with no clear guid...

In recent years, a number of systems capable of predicting future infectious disease incidence have been developed. As more of these systems are operationalized, it is important that the forecasts generated by these different approaches be formally reconciled so that individual forecast error and bias are reduced. Here we present a first example of...

Climate change is expected to impact the distribution of environmental suitability for malaria transmission by altering temperature and rainfall patterns, but the local and global impacts of climate change on malaria transmission are uncertain. To assess the effect of climate change on malaria transmission in West Africa. We coupled a detailed mech...

Low levels of relative humidity are known to decrease the lifespan of mosquitoes. However, most current models of malaria transmission do not account for the effects of relative humidity on mosquito survival. In the Sahel, where relative humidity drops to levels <20% for several months of the year, we expect relative humidity to play a significant...

Our ability to forecast epidemics far into the future is constrained by the many complexities of disease systems. Realistic longer-term projections may, however, be possible under well-defined scenarios that specify the future state of critical epidemic drivers. Since December 2020, the U.S. COVID-19 Scenario Modeling Hub (SMH) has convened multipl...

Our ability to forecast epidemics more than a few weeks into the future is constrained by the complexity of disease systems, our limited ability to measure the current state of an epidemic, and uncertainties in how human action will affect transmission. Realistic longer-term projections (spanning more than a few weeks) may, however, be possible und...

During the COVID-19 pandemic, forecasting COVID-19 trends to support planning and response was a priority for scientists and decision makers alike. In the United States, COVID-19 forecasting was coordinated by a large group of universities, companies, and government entities led by the Centers for Disease Control and Prevention and the US COVID-19...

By August 1, 2022, the SARS-CoV-2 virus had caused over 90 million cases of COVID-19 and one million deaths in the United States. Since December 2020, SARS-CoV-2 vaccines have been a key component of US pandemic response; however, the impacts of vaccination are not easily quantified. Here, we use a dynamic county-scale metapopulation model to estim...

Background The COVID-19 Scenario Modeling Hub convened nine modeling teams to project the impact of expanding SARS-CoV-2 vaccination to children aged 5–11 years on COVID-19 burden and resilience against variant strains. Methods Teams contributed state- and national-level weekly projections of cases, hospitalizations, and deaths in the United State...

By August 1, 2022, the SARS-CoV-2 virus had caused over 90 million cases of COVID-19 and one million deaths in the United States. Since December 2020, SARS-CoV-2 vaccines have been a key component of US pandemic response; however, the impacts of vaccination are not easily quantified. Here, we use a dynamic county-scale metapopulation model to estim...

In Spring 2021, the highly transmissible SARS-CoV-2 Delta variant began to cause increases in cases, hospitalizations, and deaths in parts of the United States. At the time, with slowed vaccination uptake, this novel variant was expected to increase the risk of pandemic resurgence in the US in summer and fall 2021. As part of the COVID-10 Scenario...

Background SARS-CoV-2 vaccination of persons aged 12 years and older has reduced disease burden in the United States. The COVID-19 Scenario Modeling Hub convened multiple modeling teams in September 2021 to project the impact of expanding vaccine administration to children 5-11 years old on anticipated COVID-19 burden and resilience against variant...

The COVID-19 pandemic disrupted health systems and economies throughout the world during 2020 and was particularly devastating for the United States, which experienced the highest numbers of reported cases and deaths during 20201–3. Many of the epidemiological features responsible for observed rates of morbidity and mortality have been reported4–8;...

Nearly 1 year into the coronavirus disease 2019 pandemic, the first severe acute respiratory syndrome coronavirus 2 vaccines received emergency use authorisation and vaccination campaigns began. A number of factors can reduce the averted burden of cases and deaths due to vaccination. Here, we use a dynamic model, parametrised with Bayesian inferenc...

What is already known about this topic? The highly transmissible SARS-CoV-2 Delta variant has begun to cause increases in cases, hospitalizations, and deaths in parts of the United States. With slowed vaccination uptake, this novel variant is expected to increase the risk of pandemic resurgence in the US in July-December 2021. What is added by this...

Short-term probabilistic forecasts of the trajectory of the COVID-19 pandemic in the United States have served as a visible and important communication channel between the scientific modeling community and both the general public and decision-makers. Forecasting models provide specific, quantitative, and evaluable predictions that inform short-term...

Nearly one year into the COVID-19 pandemic, the first SARS-COV-2 vaccines received emergency use authorization and vaccination campaigns began. A number of factors can reduce the averted burden of cases and deaths due to vaccination. Here, we use a dynamic model, parametrized with Bayesian inference methods, to assess the effects of non-pharmaceuti...

The COVID-19 pandemic disrupted health systems and economies throughout the world during 2020 and was particularly devastating for the United States. Many of epidemiological features that produced observed rates of morbidity and mortality have not been thoroughly assessed. Here we use a data-driven model-inference approach to simulate the pandemic...

In this communication we assess the potential benefit of SARS-COV-2 pandemic vaccination in the US and show how continued use of non-pharmaceutical interventions (NPIs) will be crucial during implementation.

The 2020 Atlantic hurricane season was extremely active and included, as of early November, six hurricanes that made landfall in the United States during the global coronavirus disease 2019 (COVID-19) pandemic. Such an event would necessitate a large-scale evacuation, with implications for the trajectory of the pandemic. Here we model how a hypothe...

Dengue is a vector-borne disease transmitted by the Aedes genus mosquito. It causes financial burdens on public health systems and considerable morbidity and mortality. Tropical regions in the Americas and Asia are the areas most affected by the virus. Fortaleza is a city with approximately 2.6 million inhabitants in northeastern Brazil that, durin...

Background The COVID-19 pandemic has driven demand for forecasts to guide policy and planning. Previous research has suggested that combining forecasts from multiple models into a single "ensemble" forecast can increase the robustness of forecasts. Here we evaluate the real-time application of an open, collaborative ensemble to forecast deaths attr...

Current projections and unprecedented storm activity to date suggest the 2020 Atlantic hurricane season will be extremely active and that a major hurricane could make landfall during the global COVID-19 pandemic. Such an event would necessitate a large-scale evacuation, with implications for the trajectory of the pandemic. Here we model how a hypot...

In March and April 2020, control measures enforcing social distancing and restricting individual movement and contact were adopted across the United States in an effort to slow the spread and growth of COVID-19. However, a number of states have now begun to ease these restrictions. Here, we evaluate the effects of loosening stay-at-home orders on C...

Seasonal influenza results in substantial annual morbidity and mortality in the United States and worldwide. Accurate forecasts of key features of influenza epidemics, such as the timing and severity of the peak incidence in a given season, can inform public health response to outbreaks. As part of ongoing efforts to incorporate data and advanced a...

A wide range of research has promised new tools for forecasting infectious disease dynamics, but little of that research is currently being applied in practice, because tools do not address key public health needs, do not produce probabilistic forecasts, have not been evaluated on external data, or do not provide sufficient forecast skill to be use...

Recent research has advanced infectious disease forecasting from an aspiration to an operational reality. The accuracy of such operational forecasting depends on the quantity and quality of observations available for system optimization. In particular, for forecasting systems that use combined mechanistic model-inference approaches, a broad suite o...

Seasonal influenza results in substantial annual morbidity and mortality in the United States and worldwide. Accurate forecasts of key features of influenza epidemics, such as the timing and severity of the peak incidence in a given season, can inform public health response to outbreaks. As part of ongoing efforts to incorporate data and advanced a...

Influenza infects an estimated 9–35 million individuals each year in the United States and is a contributing cause for between 12,000 and 56,000 deaths annually. Seasonal outbreaks of influenza are common in temperate regions of the world, with highest incidence typically occurring in colder and drier months of the year. Real-time forecasts of infl...

Influenza infects an estimated 9 to 35 million individuals each year in the United States and is a contributing cause for between 12,000 and 56,000 deaths annually. Seasonal outbreaks of influenza are common in temperate regions of the world, with highest incidence typically occurring in colder and drier months of the year. Real-time forecasts of i...

A variety of mechanistic and statistical methods to forecast seasonal influenza have been proposed and are in use; however, the effects of various data issues and design choices (statistical versus mechanistic methods, for example) on the accuracy of these approaches have not been thoroughly assessed. Here, we compare the accuracy of three forecast...

Respiratory syncytial virus (RSV) infections peak during the winter months in the United States, yet the timing, intensity, and onset of these outbreaks vary each year. An RSV vaccine is on the cusp of being released; precise models and accurate forecasts of RSV epidemics may prove vital for planning where and when the vaccine should be deployed. A...

Recent research has produced a number of methods for forecasting seasonal influenza outbreaks. However, differences among the predicted outcomes of competing forecast methods can limit their use in decision-making. Here, we present a method for reconciling these differences using Bayesian model averaging. We generated retrospective forecasts of pea...

Performance of superensemble forecasts compared to individual forecasts by influenza season. Each line shows the results of one forecast, with grey dotted lines representing the 21 individual forecasts and colored lines representing superensemble forecasts. SE-baseline refers to the baseline superensemble forecast, whereas SE-week, SE-region, SE-fo...

Additional details on forecast methods. (PDF)

Sample superensemble forecast with 95% credible intervals. The weekly SE-baseline and SE-week forecasts are shown for a sample outbreak. 95% credible intervals are indicated by the shaded areas. (TIF)

Coverage of forecast credible intervals. The points on the graph show the percent of observations falling within the specified credible intervals of the superensemble forecasts. (TIF)

Heat map of forecast rankings. Same as Fig 6 in main text of paper, but with superensemble weights stratified by lead time of forecast relative to observed outbreak peak. (TIF)

Background Africa is the hotspot for malaria transmission where more than 90% of malaria deaths occur every year. The effect of climate change on malaria transmission in Africa has been controversial. Malaria is a major vector-borne parasitic disease transmitted to humans by Anopheles spp mosquitoes. Malaria transmission is an intricate function of...

Malaria transmission is a complex system and, in many parts of the world, is closely related to climate conditions. However, studies on environmental determinants of malaria generally consider only concurrent climate conditions and ignore the historical or initial conditions of the system. Here, we demonstrate the concept of hysteresis in malaria t...

Additional details on study methods and results. Includes text, figures and tables.

Malaria transmission in West Africa is closely tied to climate, as rain fed water pools provide breeding habitat for the anopheles mosquito vector, and temperature affects the mosquito's ability to spread disease. This thesis presents a framework of highly detailed, spatially explicit mechanistic modelling to explore the relationships between the e...

Individuals continuously exposed to malaria gradually acquire immunity that protects from severe disease and high levels of parasitization. Acquired immunity has been incorporated into numerous models of malaria transmission of varying levels of complexity (e.g. Bull World Health Organ 50:347, 1974; Am J Trop Med Hyg 75:19, 2006; Math Biosci 90:385...

This thesis describes studies on the use of the Hydrology, Entomology and Malaria Transmission Simulator (HYDREMATS) developed and tested against field data by Bomblies et al. (2008) in simulating and predicting the potential for malaria transmission in rural Africa. The first study examined the temporal resolution of rainfall input required by HYD...

This paper describes the use of satellite-based estimates of rainfall to force the Hydrology, Entomology and Malaria Transmission Simulator (HYDREMATS), a hydrology-based mechanistic model of malaria transmission. We first examined the temporal resolution of rainfall input required by HYDREMATS. Simulations conducted over Banizoumbou village in Nig...

Early warnings of malaria transmission allow health officials to better prepare for future epidemics. Monitoring rainfall is recognized as an important part of malaria early warning systems. The Hydrology, Entomology and Malaria Simulator (HYDREMATS) is a mechanistic model that relates rainfall to malaria transmission, and could be used to provide...

The Hydrology, Entomology and Malaria Transmission Simulator (HYDREMATS) is a mechanistic model developed to assess malaria risk in areas where the disease is water-limited. This model relies on precipitation inputs as its primary forcing. Until now, applications of the model have used ground-based precipitation observations. However, rain gauge ne...