Understanding drivers of phylogenetic clustering and terminal branch lengths distribution in epidemics of Mycobacterium tuberculosis

Detecting factors associated with transmission is important to understand disease epidemics, and to design effective public health measures. Clustering and terminal branch lengths (TBL) analyses are commonly applied to genomic data sets of Mycobacterium tuberculosis (MTB) to identify sub-populations with increased transmission. Here, I used a simulation-based approach to investigate what epidemiological processes influence the results of clustering and TBL analyses, and whether difference in transmission can be detected with these methods. I simulated MTB epidemics with different dynamics (latency, infectious period, transmission rate, basic reproductive number R0, sampling proportion, and molecular clock), and found that all these factors, except the length of the infectious period and R0, affect the results of clustering and TBL distributions. I show that standard interpretations of this type of analyses ignore two main caveats: 1) clustering results and TBL depend on many factors that have nothing to do with transmission, 2) clustering results and TBL do not tell anything about whether the epidemic is stable, growing, or shrinking. An important consequence is that the optimal SNP threshold for clustering depends on the epidemiological conditions, and that sub-populations with different epidemiological characteristics should not be analyzed with the same threshold. Finally, these results suggest that different clustering rates and TBL distributions, that are found consistently between different MTB lineages, are probably due to intrinsic bacterial factors, and do not indicate necessarily differences in transmission or evolutionary success.

Optimizing Plant Disease Management in Agricultural Ecosystems Through Rational In-Crop Diversification

Biodiversity plays multifaceted roles in societal development and ecological sustainability. In agricultural ecosystems, using biodiversity to mitigate plant diseases has received renewed attention in recent years but our knowledge of the best ways of using biodiversity to control plant diseases is still incomplete. In term of in-crop diversification, it is not clear how genetic diversity per se in host populations interacts with identifiable resistance and other functional traits of component genotypes to mitigate disease epidemics and what is the best way of structuring mixture populations. In this study, we created a series of host populations by mixing different numbers of potato varieties showing different late blight resistance levels in different proportions. The amount of naturally occurring late blight disease in the mixture populations was recorded weekly during the potato growing seasons. The percentage of disease reduction (PDR) in the mixture populations was calculated by comparing their observed late blight levels relative to that expected when they were planted in pure stands. We found that PDR in the mixtures increased as the number of varieties and the difference in host resistance (DHR) between the component varieties increased. However, the level of host resistance in the potato varieties had little impact on PDR. In mixtures involving two varieties, the optimum proportion of component varieties for the best PDR depended on their DHR, with an increasing skewness to one of the component varieties as the DHR between the component varieties increased. These results indicate that mixing crop varieties can significantly reduce disease epidemics in the field. To achieve the best disease mitigation, growers should include as many varieties as possible in mixtures or, if only two component mixtures are possible, increase DHR among the component varieties.

Genomic and In Vitro Phenotypic Comparisons of Epidemic and Non-Epidemic Getah Virus Strains

Getah virus is an emerging mosquito-borne animal pathogen. Four phylogenetic groups of GETV, Group I (GI), GII, GIII and GIV, were identified. However, only the GETV GIII was associated with disease epidemics suggesting possible virulence difference in this virus group. Here, we compared the genetic and in vitro phenotypic characteristics between the epidemic and non-epidemic GETV. Our complete coding genome sequence analyses revealed several amino acid substitutions unique to the GETV GIII and GIV groups, which were found mainly in the hypervariable domain of nsP3 and E2 proteins. Replication kinetics of the epidemic (GIII MI-110 and GIII 14-I-605) and non-epidemic GETV strains (prototype GI MM2021 and GIV B254) were compared in mammalian Vero cells and mosquito C6/36 and U4.4 cells. In all cells used, both epidemic GETV GIII MI-110 and GIII 14-I-605 strains showed replication rates and mean maximum titers at least 2.7-fold and 2.3-fold higher than those of GIV B254, respectively (Bonferroni posttest, P<0.01). In Vero cells, the epidemic GETV strains caused more pronounced cytopathic effects in comparison to the GIV B254. Our findings suggest that higher virus replication competency to produce high virus titer during infection may be the main determinant of virulence and epidemic potential of GETV.

Data science approaches to confronting the COVID-19 pandemic: a narrative review

During the COVID-19 pandemic, more than ever, data science has become a powerful weapon in combating an infectious disease epidemic and arguably any future infectious disease epidemic. Computer scientists, data scientists, physicists and mathematicians have joined public health professionals and virologists to confront the largest pandemic in the century by capitalizing on the large-scale ‘big data’ generated and harnessed for combating the COVID-19 pandemic. In this paper, we review the newly born data science approaches to confronting COVID-19, including the estimation of epidemiological parameters, digital contact tracing, diagnosis, policy-making, resource allocation, risk assessment, mental health surveillance, social media analytics, drug repurposing and drug development. We compare the new approaches with conventional epidemiological studies, discuss lessons we learned from the COVID-19 pandemic, and highlight opportunities and challenges of data science approaches to confronting future infectious disease epidemics. This article is part of the theme issue ‘Data science approaches to infectious disease surveillance’.

MULTI-WAVE COVID-19 PANDEMIC DYNAMICS IN ICELAND IN TERMS OF DOUBLE SIGMOIDAL BOLTZMANN EQUATION (DSBE)

The world is facing multi-wave transmission of COVID-19 pandemics, and investigations are rigorously carried out on modeling the dynamics of the pandemic. Multi-wave transmission during infectious disease epidemics is a big challenge to public health. Here we introduce a simple mathematical model, the double sigmoidal-Boltzmann equation (DSBE), for analyzing the multi-wave Covid-19 spread in Iceland in terms of the number of cumulative cases. Simulation results and the main parameters that characterize multi waves are derived, yielding important information about the behavior of the multi-wave pandemics over time. The result of the current examination reveals the effectiveness and efficacy of DSBE for exploring the Covid 19 dynamics in Iceland and can be employed to examine the pandemic situation in different countries undergoing multi-waves.

COVID-19 Clinical Manifestations & Concerns among the Kingdom of Saudi Arabia's 937 Health Hotline Callers in Jeddah

The on-going COVID-19 pandemic has highlighted telehealth as a crucial tool in delivering high quality healthcare with increased efficiency. In the Kingdom of Saudi Arabia this has been evidently clear with the establishment of the robust Ministry of Health 937 COVID-19 hotline. The objectives of our study are to describe the clinical patterns of COVID-19, identify the most common concerns of the 937 hotline callers and to identify the associations between the clinical presentation of COVID-19 and risk factors of the patients.through an Analytic Cross-Sectional study design. Results : The average age was 36.8 ± 15.7 years, 61.1% were males and 38.9% were females. 69.3% were Saudi and 30.7% were non-Saudis. 82.5% employed, whilst 17.5% were unemployed.The most commonly reported symptoms were fever, followed by fatigue and cough respectively. With 41.8%, 28.2% and 23.2% of participants reporting those symptoms respectively. The most significant predictors of developing shortness of breath due to COVID-19 was chronic lung disease OR=5.7pvalue >0.01, chronic kidney disease, OR = 4.8 p value >0.02 and immunocompromised state OR = 19 >0.01. 82% of all calls to the hotline were related to COVID-19 testing, and 11% of all calls resulted in the caller receiving medical counselling and/or treatment without having to make a physical visit to a healthcare provider. Conclusion : A well-designed telehealth program can mitigate the need for a physical visit to the emergency room or clinic and as such reduce the load on front-line healthcare workers, reducing transmission and improving outcomes during infectious disease epidemics. It can also provide valuable insights into the presentation and risk factors of a new disease to aid in the prevention, diagnosis, management and control of the disease.

Welfare economics of managing an epidemic: an exposition

This paper reviews recent findings on the normative analysis of private and governmental countermeasures against infectious diseases, focusing on COVID-19. Based on a model that relates the economic activity to infectious disease epidemics, policies that maximize social welfare are considered. Lockdowns in many countries are measures that restrict economic activity over a wide area, and the economic damage they cause is extremely large. Existing studies on the net benefit of lockdown implemented in 2020 have reached mixed conclusions as to whether it is warranted or not. Although the estimates of costs and effects are relatively stable, the setting of the value of a statistical life for converting effects into benefits has a wide range and is also likely to overestimate benefits. Therefore, a careful procedure for setting is particularly crucial to obtain a reliable evaluation of countermeasures. Compared to uniform restriction of activities, taking measures to restrict activities by selecting targets may improve efficiency. Attributes that can be used to select targets include those that can be identified at little or no cost, such as age and industry, and those that can only be identified at a cost, such as close contact with infectious individuals and the presence of pathogens. In comparison to lockdown, these measures may reduce human suffering and economic suffering. No trade-off exists between uniform activity restrictions and selective activity restrictions.

Indirect transfer of pyriproxyfen to European honeybees via an autodissemination approach

The frequency of arboviral disease epidemics is increasing and vector control remains the primary mechanism to limit arboviral transmission. Container inhabiting mosquitoes such as Aedes albopictus and Aedes aegypti are the primary vectors of dengue, chikungunya, and Zika viruses. Current vector control methods for these species are often ineffective, suggesting the need for novel control approaches. A proposed novel approach is autodissemination of insect growth regulators (IGRs). The advantage of autodissemination approaches is small amounts of active ingredients compared to traditional insecticide applications are used to impact mosquito populations. While the direct targeting of cryptic locations via autodissemination seems like a significant advantage over large scale applications of insecticides, this approach could actually affect nontarget organisms by delivering these highly potent long lasting growth inhibitors such as pyriproxyfen (PPF) to the exact locations that other beneficial insects visit, such as a nectar source. Here we tested the hypothesis that PPF treated male Ae. albopictus will contaminate nectar sources, which results in the indirect transfer of PPF to European honey bees (Apis mellifera). We performed bioassays, fluorescent imaging, and mass spectrometry on insect and artificial nectar source materials to examine for intra- and interspecific transfer of PPF. Data suggests there is direct transfer of PPF from Ae. albopictus PPF treated males and indirect transfer of PPF to A. mellifera from artificial nectar sources. In addition, we show a reduction in fecundity in Ae. albopictus and Drosophila melanogaster when exposed to sublethal doses of PPF. The observed transfer of PPF to A. mellifera suggests the need for further investigation of autodissemination approaches in a more field like setting to examine for risks to insect pollinators.

Palliative care for people who use substances during communicable disease epidemics and pandemics: a scoping review protocol

IntroductionCommunicable disease epidemics and pandemics magnify the health inequities experienced by marginalised populations. People who use substances suffer from high rates of morbidity and mortality and should be a priority to receive palliative care, yet they encounter many barriers to palliative care access. Given the pre-existing inequities to palliative care access for people with life-limiting illnesses who use substances, it is important to understand the impact of communicable disease epidemics and pandemics such as COVID-19 on this population.Methods and analysisWe will conduct a scoping review and report according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews reporting guidelines. We conducted a comprehensive literature search in seven bibliographical databases from the inception of each database to August 2020. We also performed a grey literature search to identify the publications not indexed in the bibliographical databases. All the searches will be rerun in April 2021 to retrieve recently published information because the COVID-19 pandemic is ongoing at the time of this writing. We will extract the quantitative data using a standardised data extraction form and summarise it using descriptive statistics. Additionally, we will conduct thematic qualitative analyses and present our findings as narrative summaries.Ethics and disseminationEthics approval is not required for a scoping review. We will disseminate our findings to healthcare providers and policymakers through professional networks, digital communications through social media platforms, conference presentations and publication in a scientific journal.