The impact of natural disasters on the spread of COVID-19: a geospatial, agent-based epidemiology model

Background Natural disasters and infectious diseases result in widespread disruption to human health and livelihood. At the scale of a global pandemic, the co-occurrence of natural disasters is inevitable. However, the impact of natural disasters on the spread of COVID-19 has not been extensively evaluated through epidemiological modelling. Methods We create an agent-based epidemiology model based on COVID-19 clinical, epidemiological, and geographic data. We first model 35 scenarios with varying natural disaster timing and duration for a COVID-19 outbreak in a theoretical region. We then evaluate the potential effect of an eruption of Vesuvius volcano on the spread of COVID-19 in Campania, Italy. Results In a majority of cases, the occurrence of a natural disaster increases the number of disease related fatalities. For a natural disaster fifty days after infection onset, the median increase in fatalities is 2, 59, and 180% for a 2, 14, and 31-day long natural disaster respectively, when compared to the no natural disaster scenario. For the Campania case, the median increase in fatalities is 1.1 and 2.4 additional fatalities per 100,000 for eruptions on day 1 and 100 respectively, and 60.0 additional fatalities per 100,000 for an eruption close to the peak in infections (day 50). Conclusion Our results show that the occurrence of a natural disaster in most cases leads to an increase in infection related fatalities, with wide variance in possible outcomes depending on the timing of the natural disaster relative to the peak in infections and the duration of the natural disaster.

Assessing countermeasures during a hepatitis A virus outbreak among men who have sex with men

Background A hepatitis A epidemic occurred among men who have sex with men (MSM) in Japan in 2017–2018. In this study, we employ a parsimonious mathematical model to epidemiologically investigate the dynamics of infection, aiming to evaluate the effectiveness of campaign-based interventions among MSM to raise awareness of the situation. Methods A mathematical model describing a mixture of human-to-human transmission and environmental transmission was fitted to surveillance data. Taking seasonally varying environmental transmission into account, we estimated the reproduction number of hepatitis A virus during the course of epidemic, and, especially, the abrupt decline in this reproduction number following campaign-based interventions. Results The reproduction number prior to the countermeasures ranged from 2.6 to 3.1 and then began to decrease following campaign-based interventions. After the first countermeasure, the reproduction number decreased, but the epidemic remained supercritical (i.e., Rt > 1). The value of Rt dropped well below one following the second countermeasure, which used web articles to widely disseminate information about the epidemic risk. Conclusions Although the effective reproduction number, Rt, changes because of both intrinsic and extrinsic factors, the timing of the examined countermeasures against hepatitis A in the MSM population was consistent with the abrupt declines observed in Rt. Even without vaccination, the epidemic was brought under control, and risky behaviors may have been changed by the increase in situation awareness reached through web articles.

The effect of men who have sex with men (MSM) on the spread of sexually transmitted infections

Sexually transmitted infections (STIs) have remained a worldwide public health threat. It is difficult to control the spread of STIs, not only because of heterogeneous sexual transmission between men and women but also because of the complicated effects of sexual transmission among men who have sex with men (MSM) and mother-to-child transmission. Many studies point to the existence of a ‘bisexual bridge’, where STIs spread from the MSM network via bisexual connections. However, it is unclear how the MSM network affects heterosexual networks as well as mother-to-child transmission. To analyse the effect of MSM on the spread of STIs, we divided the population into four subpopulations: (i) women, (ii) men who have sex with women only (MSW), (iii) men who have sex with both men and women (MSMW), (iv) men who have sex with men exclusively (MSME). We calculated the type-reproduction numbers of these four subpopulations, and our analysis determined what preventive measures may be effective. Our analysis shows the impact of bisexual bridge on the spread of STIs does not outweigh their population size. Since MSM and mother-to-child transmission rates do not have a strong synergistic effect when combined, complementary prevention measures are needed. The methodologies and findings we have provided here will contribute greatly to the future development of public health.

Analysis of international traveler mobility patterns in Tokyo to identify geographic foci of dengue fever risk

Travelers play a role in triggering epidemics of imported dengue fever because they can carry the virus to other countries during the incubation period. If a traveler carrying dengue virus visits open green space and is bitten by mosquitoes, a local outbreak can ensue. In the present study, we aimed to understand the movement patterns of international travelers in Tokyo using mobile phone data, with the goal of identifying geographical foci of dengue transmission. We analyzed datasets based on mobile phone access to WiFi systems and measured the spatial distribution of international visitors in Tokyo on two specific dates (one weekday in July 2017 and another weekday in August 2017). Mobile phone users were classified by nationality into three groups according to risk of dengue transmission. Sixteen national parks were selected based on their involvement in a 2014 dengue outbreak and abundance of Aedes mosquitoes. We found that not all national parks were visited by international travelers and that visits to cemeteries were very infrequent. We also found that travelers from countries with high dengue prevalence were less likely to visit national parks compared with travelers from dengue-free countries. Travelers from countries with sporadic dengue cases and countries with regional transmission tended to visit common destinations. By contrast, the travel footprints of visitors from countries with continuous dengue transmission were focused on non-green spaces. Entomological surveillance in Tokyo has been restricted to national parks since the 2014 dengue outbreak. However, our results indicate that areas subject to surveillance should include both public and private green spaces near tourist sites.

Markov modelling of viral load adjusting for CD4 orthogonal variable and multivariate conditional autoregressive mapping of the HIV immunological outcomes among ART patients in Zimbabwe

Background This study aimed to jointly model HIV disease progression patterns based on viral load (VL) among adult ART patients adjusting for the time-varying “incremental transients states” variable, and the CD4 cell counts orthogonal variable in a single 5-stage time-homogenous multistate Markov model. We further jointly mapped the relative risks of HIV disease progression outcomes (detectable VL (VL ≥ 50copies/uL) and immune deterioration (CD4 < 350cells/uL) at the last observed visit) conditional not to have died or become loss to follow-up (LTFU). Methods Secondary data analysis of individual-level patients on ART was performed. Adjusted transition intensities, hazard ratios (HR) and regression coefficients were estimated from the joint multistate model of VL and CD4 cell counts. The mortality and LTFU transition rates defined the extent of patients’ retention in care. Joint mapping of HIV disease progression outcomes after ART initiation was done using the Bayesian intrinsic Multivariate Conditional Autoregressive prior model. Results The viral rebound from the undetectable state was 1.78times more likely compared to viral suppression among patients with VL ranging from 50-1000copies/uL. Patients with CD4 cell counts lower than expected had a higher risk of viral increase above 1000copies/uL and death if their VL was above 1000copies/uL (state 2 to 3 (λ23): HR = 1.83 and (λ34): HR = 1.42 respectively). Regarding the time-varying effects of CD4 cell counts on the VL transition rates, as the VL increased, (λ12 and λ23) the transition rates increased with a decrease in the CD4 cell counts over time. Regardless of the individual’s VL, the transition rates to become LTFU decreased with a decrease in CD4 cell counts. We observed a strong shared geographical pattern of 66% spatial correlation between the relative risks of detectable VL and immune deterioration after ART initiation, mainly in Matabeleland North. Conclusion With high rates of viral rebound, interventions which encourage ART adherence and continual educational support on the barriers to ART uptake are crucial to achieve and sustain viral suppression to undetectable levels. Area-specific interventions which focus on early ART screening through self-testing, behavioural change campaigns and social support strategies should be strengthened in heavily burdened regions to sustain the undetectable VL. Sustaining undetectable VL lowers HIV transmission in the general population and this is a step towards achieving zero HIV incidences by 2030.

On the relationship between inhibition and receptor occupancy by nondepolarizing neuromuscular blocking drugs

Background Nondepolarizing neuromuscular blocking drugs (NDNBs) are clinically used to produce muscle relaxation during general anesthesia. To better understand clinical properties of NDNBs, comparative in vitro pharmacologic studies have been performed. In these studies, a receptor binding model, which relies on the assumption that the inhibition, i.e., the effect of an NDNB, is proportional to the receptor occupancy by the drug, has been effectively used to describe obtained experimental data. However, it has not been studied in literature under which conditions the above assumption can be justified nor the assumption still holds in vivo. The purpose of this study is to explore the in vivo relationship between the inhibition and the receptor occupancy by an NDNB and to draw implications on how in vitro experimental results can be used to discuss the in vivo properties of NDNBs. Methods An ordinary differential equation model is employed to simulate physiologic processes of the activation of receptors by acetylcholine (ACh) as well as inhibition by an NDNB. With this model, the degree of inhibition is quantified by the fractional amount of receptors that are not activated by ACh due to the presence of an NDNB. The results are visualized by plotting the fractional amounts of the activated receptors as a function of the receptor occupancy. Results Numerical investigations reflecting in vivo conditions show that the degree of inhibition is not proportional to the receptor occupancy, i.e., there is a nonlinear relationship between the inhibition and the receptor occupancy. However, under a setting of high concentration of ACh reflecting a typical situation of in vitro experiments, the relationship between the inhibition and the receptor occupancy becomes linear, suggesting the validity of the receptor binding model. Also, it is found that the extent of nonlinearity depends on the selectivity of NDNBs for the two binding sites of the receptors. Conclusions While the receptor binding model may be effective for estimating affinity of an NDNB through in vitro experiments, these models do not directly describe in vivo properties of NDNBs, because the nonlinearity between the inhibition and the receptor occupancy causes the modulation of the resultant concentration-effect relationships of NDNBs.

Modelling the impact of delaying vaccination against SARS-CoV-2 assuming unlimited vaccine supply

Background At the moment we have more than 177 million cases and 3.8 million deaths (as of June 2021) around the world and vaccination represents the only hope to control the pandemic. Imperfections in planning vaccine acquisition and difficulties in implementing distribution among the population, however, have hampered the control of the virus so far. Methods We propose a new mathematical model to estimate the impact of vaccination delay against the 2019 coronavirus disease (COVID-19) on the number of cases and deaths due to the disease in Brazil. We apply the model to Brazil as a whole and to the State of Sao Paulo, the most affected by COVID-19 in Brazil. We simulated the model for the populations of the State of Sao Paulo and Brazil as a whole, varying the scenarios related to vaccine efficacy and compliance from the populations. Results The model projects that, in the absence of vaccination, almost 170 thousand deaths and more than 350 thousand deaths will occur by the end of 2021 for Sao Paulo and Brazil, respectively. If in contrast, Sao Paulo and Brazil had enough vaccine supply and so started a vaccination campaign in January with the maximum vaccination rate, compliance and efficacy, they could have averted more than 112 thousand deaths and 127 thousand deaths, respectively. In addition, for each month of delay the number of deaths increases monotonically in a logarithmic fashion, for both the State of Sao Paulo and Brazil as a whole. Conclusions Our model shows that the current delay in the vaccination schedules that is observed in many countries has serious consequences in terms of mortality by the disease and should serve as an alert to health authorities to speed the process up such that the highest number of people to be immunized is reached in the shortest period of time.

Estimating COVID-19 cases infected with the variant alpha (VOC 202012/01): an analysis of screening data in Tokyo, January-March 2021

Background In Japan, a part of confirmed patients’ samples have been screened for the variant of concern (VOC), including the variant alpha with N501Y mutation. The present study aimed to estimate the actual number of cases with variant alpha and reconstruct the epidemiological dynamics. Methods The number of cases with variant alpha out of all PCR confirmed cases was estimated, employing a hypergeometric distribution. An exponential growth model was fitted to the growth data of variant alpha cases over fourteen weeks in Tokyo. Results The weekly incidence with variant alpha from 18–24 January 2021 was estimated at 4.2 (95% confidence interval (CI): 0.7, 44.0) cases. The expected incidence in early May ranged from 420–1120 cases per week, and the reproduction number of variant alpha was on the order of 1.5 even under the restriction of contact from January-March, 2021, Tokyo. Conclusions The variant alpha was predicted to swiftly dominate COVID-19 cases in Tokyo, and this has actually occurred by May 2021. Devising the proposed method, any country or location can interpret the virological sampling data.

Exploring secondary SARS-CoV-2 transmission from asymptomatic cases using contact tracing data

Background Individuals with asymptomatic severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection can propagate the virus unknowingly and thus have been a focus of public health attentions since the early stages of the pandemic. Understanding viral transmissibility among asymptomatic individuals is critical for successful control of coronavirus disease 2019 (COVID-19). The present study aimed to understand SARS-CoV-2 transmissibility among young asymptomatic individuals and to assess whether symptomatology was associated with transmission of symptomatic vs. asymptomatic infections. Methods We analyzed one of the first-identified clusters of SARS-CoV-2 infections with multiple chains of transmission that occurred among university students in March 2020 in Kyoto prefecture, Japan, using discrete and two-type branching process models. Assuming that the number of secondary cases resulting from either primary symptomatic or asymptomatic cases independently followed negative binomial distributions, we estimated the relative reproduction numbers of an asymptomatic case compared with a symptomatic case. To explore the potential association between symptomatology and transmission of symptomatic vs. asymptomatic incident infections, we also estimated the proportion of secondary symptomatic cases produced by primary symptomatic and asymptomatic cases. Results The reproduction number for a symptomatic primary case was estimated at 1.14 (95% confidence interval [CI]: 0.61–2.09). The relative reproduction number for asymptomatic cases was estimated at 0.19 (95% CI: 0.03–0.66), indicating that asymptomatic primary cases did not result in sufficient numbers of secondary infections to maintain chains of transmission. There was no apparent tendency for symptomatic primary cases to preferentially produce symptomatic secondary cases. Conclusions Using data from a transmission network during the early epidemic in Japan, we successfully estimated the relative transmissibility of asymptomatic cases of SARS-CoV-2 infection at 0.22. These results suggest that contract tracing focusing on symptomatic index cases may be justified given limited testing capacity.

How mathematical modeling could contribute to the quantification of metastatic tumor burden under therapy: insights in immunotherapeutic treatment of non-small cell lung cancer

Background Cancer is one of the leading death causes globally with about 8.2 million deaths per year and an increase in numbers in recent years. About 90% of cancer deaths do not occur due to primary tumors but due to metastases, of which most are not clinically identifiable because of their relatively small size at primary diagnosis and limited technical possibilities. However, therapeutic decisions are formed depending on the existence of metastases and their properties. Therefore non-identified metastases might have huge influence in the treatment outcome. The quantification of clinically visible and invisible metastases is important for the choice of an optimal treatment of the individual patient as it could clarify the burden of non-identifiable tumors as well as the future behavior of the cancerous disease. Results The mathematical model presented in this study gives insights in how this could be achieved, taking into account different treatment possibilities and therefore being able to compare therapy schedules for individual patients with different clinical parameters. The framework was tested on three patients with non-small cell lung cancer, one of the deadliest types of cancer worldwide, and clinical history including platinum-based chemotherapy and PD-L1-targeted immunotherapy. Results yield promising insights into the framework to establish methods to quantify effects of different therapy methods and prognostic features for individual patients already at stage of primary diagnosis.