The Boni Lab investigates these different data points and data streams with methods at the interface of field, clinical, and computational epidemiology. We are active in applied public health research, and are integrated into public health decision making processes in several national and international organizations. From 2008 to 2016, we were based at the Oxford University Clinical Research Unit in Ho Chi Minh City, and from 2016 to 2023 we were based at the Center for Infectious Disease Dynamics, Department of Biology, Pennsylvania State University.
As of January 2024, we are located in Sunny Philadelphia — at Temple University’s Department of Biology and part of Temple’s Institute for Genomics and Evolutionary Medicine.
Current Collaborations
Artemisinin Resistance Response in Africa
Since 2020, we have been funded by the Bill and Melinda Gates Foundation and the NIH to work with the World Health Organization and partner countries in Africa on formulating response strategies to the emergence of artemisinin resistance in Africa. This includes technical consultations for the WHO’s Global Malaria Programme, and drug deployment strategy evaluations with National Malaria Control Programmes in Africa. Four country partnerships are funded so far — read here for some background on the general strategy for mitigating drug-resistance spread.
Strategy Analysis for Antimalarial Drug Policy in Rwanda and Tanzania
Our most advanced drug policy analysis has been carried out with partners in Rwanda (started early 2022) and Tanzania (started late 2023). Together with these countries’ national malaria programs, the Rwanda Biomedical Center, the President’s Malaria Initiative in Tanzania, and the National Institute for Medical Research in Tanzania, we have evaluated more than 100 potential malaria treatment strategies and evaluated their impacts over the next 5-10 years. The first published results from this work can be seen here. Analyses on geographic drug distribution in Rwanda and the effect of the private market drug use in Tanzania will be posted in late 2024.
Controlling Respiratory Disease in the Tropics
For 15 years, we have been working with the Oxford University Clinical Research Unit in Vietnam, as well as Vietnam’s National Institute for Hygiene and Epidemiology on influenza virus epidemiology and general respiratory disease surveillance. This work has ranged from seroepidemiology — recent work with the Bloom Lab shows how different age groups exert different types of selection pressure on influenza — to disease dynamics analyses of the unpredictable patterns of annual and non-annual cycles of respiratory disease in Vietnam. Our most recent work looks at the supply constrains of vaccine distribution in tropical contexts.
DeTACT
In 2019, the DeTACT trial — “Developing Triple Artemisinin Combination Therapies” — began recruiting patients in Asia and Africa. The trial is led by PI Arjen Dondorp from the Mahidol-Oxford Research Unit in Bangkok. With recruitment complete in early 2024, results should be available by year’s end. We are leading the mathematical modeling work package whose aim is to assess the risks of drug resistance emerging to triple ACTs and optimal population-level deployment strategies once TACTs are approved. The first modeling assessments of triple ACTs can be seen here in Nat Med and Nat Commun, and a third analysis with a 25-locus model will be posted in late 2024.
Research Areas
Influenza in the Tropics
From 2008 to 2019, the majority of our research questions fell under the umbrella of tropical influenza epidemiology. We looked at the circulation of human or “seasonal” influenza viruses in the tropics as well as the ecology, evolution, human behavior influences on avian influenza viruses (including factors linked with human exposure). We ran both field and clinical studies in southern Vietnam. Our laboratory methods focused on identifying antibody repertoires and viral sequences, and our analytical methods on these data are still rooted in mathematical modeling and fitting models with likelihood methods. Our key goals have been to characterize influenza’s persistence patterns, its seasonal patterns (or lack thereof), the relationship between influenza circulation and other respiratory viruses, the symptomatic/asymptomatic nature of influenza epidemics in Vietnam, and vaccination planning in this challenging context.
Multiple First-line Therapies for Malaria
The area of the most direct public health relevance that we work in is analysis and optimization of population-level treatment strategies for malaria. A balance must be struck when designing a population-level treatment strategy, as high levels of treatment drive drug resistance evolution but low levels are associated with high morbidity and mortality. One method of lowering the risk of resistance evolution to an individual drug, while maintaining high treatment rates in the population as a whole, is to deploy multiple drugs simultaneously in the population. Our epidemiological microsimulations have shown that recommending simultaneous use of multiple first-line therapies (MFT) for malaria is a better public health strategy that the status quo approach. We are currently, as of 2022-2024, actively engaged with WHO and several partner countries in Africa on making the implementation of MFT a reality.
Big-data Seroepidemiology
Since the 2009 influenza pandemic, repeated cross-sectional seroepidemiological study designs have become a common way to explore the dynamics of infection, susceptibility, and post-infection antibody responses. In southern Vietnam, we established a study in which periodic collections of population-representative serum are collected every few months, and we are currently testing for the presence of influenza antibody in these samples. The resulting data set is structured as a serological time series, or an antibody time series, and it allows for the inference of past disease dynamics if the underlying epidemiological models of infleunza transmission are believed to be correct. The inferential process reconstructs complete disease dynamics, i.e. the dynamics of symptomatic, subclinical, and asymptomatic influenza infections.
Participatory Epidemiology
One of our key study frameworks for understanding the dynamics of respiratory disease in the tropics was a community network of general practitioners in Ho Chi Minh City who send out daily reports of case numbers of influenza-like illness (ILI) by standard SMS text messages. Over ten years, more than 66,000 ILI data points were collected, providing unprecedented resolution for the ups and downs of respiratory disease incidence in a place where there is no winter to synchronize all respiratory disease into a short and intense transmission season. The scale of this community study enabled us to develop methods to determine if there was any random data entry into our system (i.e. garbage input), to determine if some clinicians were underdiagnosing or overdiagnosing influenza infections, and to validate if the macrotrends observed in our study matched those of national-level sentinel surveillance. Our results indicated that respiratory disease peaks were non-annual and that ILI trends and influenza trends did not correlate. Influenza surveillance systems in the tropics need to place an emphasis on molecular confirmation over syndromic surveillance, and incidence of other respiratory viruses will need to be studied in more detail to determine the major causes of non-influenza ILI peaks.
Recombination Detection
Part of our work is focused in bioinformatics, and the key tool that we have been maintaining for nearly twenty years is the recombination detection algorithm 3SEQ along with an online statistical calculator that can be used more generally to test the null hypothesis of “no mosaicism” in any type of string or sequence. The statistical test used in this tool is a non-parametric test for detecting clustering in one dimension (also called anomalous interval detection). It simply detects if one set of binary observations is clustered in the middle of second set of binary observations, and it can be viewed as a two-breakpoint version of the Mann-Whitney U-test or the Wilcoxon Rank-Sum test. The most recent development from this work is (since 2020) is the identification of non-recombinant regions (NRRs) or breakpoint-free regions (BFRs) which helps in origin analysis for pathogens, particularly for emergence events and novel disease outbreaks.
Epidemiological Theory
All of our work is founded in epidemiological theory. In addition to the field, clinical, and sequence based work that we do, we try to keep up with and contribute to the literature on study design, pathogen ecology and evolution, evolutionary epidemiology, and economic epidemiology. Our malaria work is rooted in the theory that evolutionary adaptation is slow in variable environments. Presenting the malaria parasite with simultaneous multiple lethal challenges should make it difficult for the parasite to evolve resistance to all of them. Likewise, part of our influenza work seeks to test the theory that long chains of influenza transmission in the tropics afford the virus more opportunity to accumulate the necessary genetic mutations to escape population immunity through antigenic drift. Testing this hypothesis requires a time series of population immunity, virus sequences, and case numbers – something we have been working towards over the past five years. The most understudied area of epidemiological theory is the piece that links human behavior with epidemic outbreaks and response. Some of our work has aimed to create a theoretical framework explaining certain economic behaviors seen in animal disease models where the animals are a source of both risk and profit.