How to make epidemiological training infectious

CITATION: Bellan, S. E. et al. 2012. How to make epidemiological training infectious. PLoS Biology, 10(4): e1001295, doi:10.1371/journal.pbio.1001295.The original publication is available at http://journals.plos.org/plosbiologyModern infectious disease epidemiology builds on two independently developed fields: classical epidemiology and dynamical epidemiology. Over the past decade, integration of the two fields has increased in research practice, but training options within the fields remain distinct with few opportunities for integration in the classroom. The annual Clinic on the Meaningful Modeling of Epidemiological Data (MMED) at the African Institute for Mathematical Sciences has begun to address this gap. MMED offers participants exposure to a broad range of concepts and techniques from both epidemiological traditions. During MMED 2010 we developed a pedagogical approach that bridges the traditional distinction between classical and dynamical epidemiology and can be used at multiple educational levels, from high school to graduate level courses. The approach is hands-on, consisting of a real-time simulation of a stochastic outbreak in course participants, including realistic data reporting, followed by a variety of mathematical and statistical analyses, stemming from both epidemiological traditions. During the exercise, dynamical epidemiologists developed empirical skills such as study design and learned concepts of bias while classical epidemiologists were trained in systems thinking and began to understand epidemics as dynamic nonlinear processes. We believe this type of integrated educational tool will prove extremely valuable in the training of future infectious disease epidemiologists. We also believe that such interdisciplinary training will be critical for local capacity building in analytical epidemiology as Africa continues to produce new cohorts of well-trained mathematicians, statisticians, and scientists. And because the lessons draw on skills and concepts from many fields in biology—from pathogen biology, evolutionary dynamics of host–pathogen interactions, and the ecology of infectious disease to bioinformatics, computational biology, and statistics—this exercise can be incorporated into a broad array of life sciences courses.http://journals.plos.org/plosbiology/article?id=10.1371/journal.pbio.1001295Publisher's versio

The role of remdesivir in South Africa : preventing COVID-19 deaths through increasing intensive care unit capacity

CITATION: Nichols, B. E. et al. 2020. The Role of Remdesivir in South Africa: Preventing COVID-19 Deaths Through Increasing Intensive Care Unit Capacity. Clinical Infectious Diseases: 72(9), 1642–1644, doi:10.1093/cid/ciaa937The original publication is available at https://academic.oup.com/cid/Countries such as South Africa have limited intensive care unit (ICU) capacity to handle the expected number of patients with COVID-19 requiring ICU care. Remdesivir can prevent deaths in countries such as South Africa by decreasing the number of days people spend in ICU, therefore freeing up ICU bed capacity.https://academic.oup.com/cid/article/72/9/1642/5868030?login=truePublishers versio

Agricultural intensification, priming for persistence and the emergence of Nipah virus: a lethal bat-borne zoonosis

Emerging zoonoses threaten global health, yet the processes by which they emerge are complex and poorly understood. Nipah virus (NiV) is an important threat owing to its broad host and geographical range, high case fatality, potential for human-to-human transmission and lack of effective prevention or therapies. Here, we investigate the origin of the first identified outbreak of NiV encephalitis in Malaysia and Singapore. We analyse data on livestock production from the index site (a commercial pig farm in Malaysia) prior to and during the outbreak, on Malaysian agricultural production, and from surveys of NiV's wildlife reservoir (flying foxes). Our analyses suggest that repeated introduction of NiV from wildlife changed infection dynamics in pigs. Initial viral introduction produced an explosive epizootic that drove itself to extinction but primed the population for enzootic persistence upon reintroduction of the virus. The resultant within-farm persistence permitted regional spread and increased the number of human infections. This study refutes an earlier hypothesis that anomalous El Niño Southern Oscillation-related climatic conditions drove emergence and suggests that priming for persistence drove the emergence of a novel zoonotic pathogen. Thus, we provide empirical evidence for a causative mechanism previously proposed as a precursor to widespread infection with H5N1 avian influenza and other emerging pathogens

Key questions for modelling COVID-19 exit strategies

Combinations of intense non-pharmaceutical interventions ('lockdowns') were introduced in countries worldwide to reduce SARS-CoV-2 transmission. Many governments have begun to implement lockdown exit strategies that allow restrictions to be relaxed while attempting to control the risk of a surge in cases. Mathematical modelling has played a central role in guiding interventions, but the challenge of designing optimal exit strategies in the face of ongoing transmission is unprecedented. Here, we report discussions from the Isaac Newton Institute 'Models for an exit strategy' workshop (11-15 May 2020). A diverse community of modellers who are providing evidence to governments worldwide were asked to identify the main questions that, if answered, will allow for more accurate predictions of the effects of different exit strategies. Based on these questions, we propose a roadmap to facilitate the development of reliable models to guide exit strategies. The roadmap requires a global collaborative effort from the scientific community and policy-makers, and is made up of three parts: i) improve estimation of key epidemiological parameters; ii) understand sources of heterogeneity in populations; iii) focus on requirements for data collection, particularly in Low-to-Middle-Income countries. This will provide important information for planning exit strategies that balance socio-economic benefits with public health

Recasting the theory of mosquito-borne pathogen transmission dynamics and control

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\u27s 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

Inference results for comparing the transmissibility of primary and secondary cases for smallpox in Europe, 1958–1973.

<p>The layout is analogous to <a href="http://www.plospathogens.org/article/info:doi/10.1371/journal.ppat.1004452#ppat-1004452-t001" target="_blank">Table 1</a>. There were a total of 36 primary cases and 537 secondary cases.</p><p>Inference results for comparing the transmissibility of primary and secondary cases for smallpox in Europe, 1958–1973.</p

Six ways of modeling the transmission of two populations whose transmissibility is being compared.

<p>The dashed lines distinguish the models according the assumptions that are made about whether and the dispersion parameter are the same or different for the two populations. The axis on the right indicates the number of parameters used in each model. This is the sum of the number of parameters used to model (either 1 or 2) and the number of parameters used to model dispersion (either 0, 1 or 2).</p

Comparing the transmissibility of primary and secondary cases for smallpox in Europe, 1958–1973.

<p>The layout is analogous to <a href="http://www.plospathogens.org/article/info:doi/10.1371/journal.ppat.1004452#ppat-1004452-g002" target="_blank">Figure 2</a> except the axes distinguish between transmission of primary and secondary cases. The inset of panel A replicates the results when and are inferred separately (our preferred model), except that the y-axis is now the ratio of to . For panels B and C, the data is shown only for cases where there was a clear record of subsequent secondary infections (as opposed to knowing that four cases lead to ten secondary cases in aggregate). The 95% confidence intervals were found by parametric bootstrap on this more limited data set.</p

Comparing animal-to-human and human-to-human transmissibility for human monkeypox in the Democratic Republic of Congo, 1981–1984.

<p>The layout is analogous to <a href="http://www.plospathogens.org/article/info:doi/10.1371/journal.ppat.1004452#ppat-1004452-g005" target="_blank">Figure 5</a>, but now the axes distinguish between animal and human transmission of monkeypox. The data shown in panel C is limited to instances where the transmission links could be unambiguously counted.</p

Inference results for comparing animal-to-human and human-to-human transmissibility for human monkeypox in the Democratic Republic of Congo, 1981–1984.

<p>The layout is analogous to <a href="http://www.plospathogens.org/article/info:doi/10.1371/journal.ppat.1004452#ppat-1004452-t001" target="_blank">Table 1</a>. The model was the preferred model since is within two of the model with the best value, indicating there is not sufficient statistical support for distinct reproduction numbers. There were a total of 125 animal exposures leading to at least one primary case and 209 human cases. Despite the size of the data set, the values are all quite small because there are large confidence intervals associated with the use of a truncated negative binomial distribution for inference <a href="http://www.plospathogens.org/article/info:doi/10.1371/journal.ppat.1004452#ppat.1004452-Blumberg1" target="_blank">[19]</a>.</p><p>Inference results for comparing animal-to-human and human-to-human transmissibility for human monkeypox in the Democratic Republic of Congo, 1981–1984.</p