Variable screening methods in spatial infectious disease transmission models.

Data-driven mathematical modelling can enrich our understanding of infectious disease spread enormously. Individual-level models of infectious disease transmission allow the incorporation of different individual-level covariates, such as spatial location, vaccination status, etc. This study aims to explore and develop methods for fitting such models when we have many potential covariates to include in the model. The aim is to enhance the performance and interpretability of models and ease the computational burden of fitting these models to data. We have applied and compared multiple variable selection methods in the context of spatial epidemic data. These include a Bayesian two-stage least absolute shrinkage and selection operator (Lasso), forward and backward stepwise selection based on the Akaike information criterion (AIC), spike-and-slab priors, and random variable selection (boosting) methods. We discuss and compare the performance of these methods via simulated datasets and UK 2001 foot-and-mouth disease data. While comparing the variable selection methods all performed consistently well except the two-stage Lasso. We conclude that the spike-and-slab prior method is to be recommended, consistently resulting in high accuracy and short computational time.

Intracerebral Hemorrhage Among Blood Donors and Their Transfusion Recipients.

Importance: Recent reports have suggested that cerebral amyloid angiopathy, a common cause of multiple spontaneous intracerebral hemorrhages (ICHs), may be transmissible through parenteral injection of contaminated cadaveric pituitary hormone in humans. Objective: To determine whether spontaneous ICH in blood donors after blood donation is associated with development of spontaneous ICH in transfusion recipients. Design, Setting, and Participants: Exploratory retrospective cohort study using nationwide blood bank and health register data from Sweden (main cohort) and Denmark (validation cohort) and including all 1 089 370 patients aged 5 to 80 years recorded to have received a red blood cell transfusion from January 1, 1970 (Sweden), or January 1, 1980 (Denmark), until December 31, 2017. Exposures: Receipt of red blood cell transfusions from blood donors who subsequently developed (1) a single spontaneous ICH, (2) multiple spontaneous ICHs, or (3) no spontaneous ICH. Main Outcomes and Measures: Spontaneous ICH in transfusion recipients; ischemic stroke was a negative control outcome. Results: A total of 759 858 patients from Sweden (median age, 65 [IQR, 48-73] years; 59% female) and 329 512 from Denmark (median age, 64 [IQR, 50-73] years; 58% female) were included, with a median follow-up of 5.8 (IQR, 1.4-12.5) years and 6.1 (IQR, 1.5-11.6) years, respectively. Patients who underwent transfusion with red blood cell units from donors who developed multiple spontaneous ICHs had a significantly higher risk of a single spontaneous ICH themselves, compared with patients receiving transfusions from donors who did not develop spontaneous ICH, in both the Swedish cohort (unadjusted incidence rate [IR], 3.16 vs 1.12 per 1000 person-years; adjusted hazard ratio [HR], 2.73; 95% CI, 1.72-4.35; P < .001) and the Danish cohort (unadjusted IR, 2.82 vs 1.09 per 1000 person-years; adjusted HR, 2.32; 95% CI, 1.04-5.19; P = .04). No significant difference was found for patients receiving transfusions from donors who developed a single spontaneous ICH in the Swedish cohort (unadjusted IR, 1.35 vs 1.12 per 1000 person-years; adjusted HR, 1.06; 95% CI, 0.84-1.36; P = .62) nor the Danish cohort (unadjusted IR, 1.36 vs 1.09 per 1000 person-years; adjusted HR, 1.06; 95% CI, 0.70-1.60; P = .73), nor for ischemic stroke as a negative control outcome. Conclusions and Relevance: In an exploratory analysis of patients who received red blood cell transfusions, patients who underwent transfusion with red blood cells from donors who later developed multiple spontaneous ICHs were at significantly increased risk of spontaneous ICH themselves. This may suggest a transfusion-transmissible agent associated with some types of spontaneous ICH, although the findings may be susceptible to selection bias and residual confounding, and further research is needed to investigate if transfusion transmission of cerebral amyloid angiopathy might explain this association.

Impact of human contact patterns on epidemic spreading in time-varying networks.

Human contact behaviors involve both dormant and active processes. The dormant (active) process goes from the disappearance (creation) to the creation (disappearance) of an edge. The dormant (active) time is the elapsed time since the edge became dormant (active). Many empirical studies have revealed that dormant and active times in human contact behaviors tend to show a long-tailed distribution. Previous researches focused on the impact of the dormant process on spreading dynamics. However, the epidemic spreading happens on the active process. This raises the question of how the active process affects epidemic spreading in complex networks. Here, we propose a novel time-varying network model in which the distributions of both the dormant time and active time of edges are adjustable. We develop a pairwise approximation method to describe the spreading dynamical processes in the time-varying networks. Through extensive numerical simulations, we find that the epidemic threshold is proportional to the mean dormant time and inversely proportional to the mean active time. The attack rate decreases with the increase of mean dormant time and increases with the increase of mean active time. It is worth noting that the epidemic threshold and the attack rate (e.g., the infected density in the steady state) are independent of the heterogeneities of the dormant time distribution and the active time distribution. Increasing the heterogeneity of the dormant time distribution accelerates epidemic spreading while increasing the heterogeneity of the active time distribution slows it down.

Extensions of mean-field approximations for environmentally-transmitted pathogen networks.

Many pathogens spread via environmental transmission, without requiring host-to-host direct contact. While models for environmental transmission exist, many are simply constructed intuitively with structures analogous to standard models for direct transmission. As model insights are generally sensitive to the underlying model assumptions, it is important that we are able understand the details and consequences of these assumptions. We construct a simple network model for an environmentally-transmitted pathogen and rigorously derive systems of ordinary differential equations (ODEs) based on different assumptions. We explore two key assumptions, namely homogeneity and independence, and demonstrate that relaxing these assumptions can lead to more accurate ODE approximations. We compare these ODE models to a stochastic implementation of the network model over a variety of parameters and network structures, demonstrating that with fewer restrictive assumptions we are able to achieve higher accuracy in our approximations and highlighting more precisely the errors produced by each assumption. We show that less restrictive assumptions lead to more complicated systems of ODEs and the potential for unstable solutions. Due to the rigour of our derivation, we are able to identify the reason behind these errors and propose potential resolutions.

Impact of urban structure on infectious disease spreading.

The ongoing SARS-CoV-2 pandemic has been holding the world hostage for several years now. Mobility is key to viral spreading and its restriction is the main non-pharmaceutical interventions to fight the virus expansion. Previous works have shown a connection between the structural organization of cities and the movement patterns of their residents. This puts urban centers in the focus of epidemic surveillance and interventions. Here we show that the organization of urban flows has a tremendous impact on disease spreading and on the amenability of different mitigation strategies. By studying anonymous and aggregated intra-urban flows in a variety of cities in the United States and other countries, and a combination of empirical analysis and analytical methods, we demonstrate that the response of cities to epidemic spreading can be roughly classified in two major types according to the overall organization of those flows. Hierarchical cities, where flows are concentrated primarily between mobility hotspots, are particularly vulnerable to the rapid spread of epidemics. Nevertheless, mobility restrictions in such types of cities are very effective in mitigating the spread of a virus. Conversely, in sprawled cities which present many centers of activity, the spread of an epidemic is much slower, but the response to mobility restrictions is much weaker and less effective. Investing resources on early monitoring and prompt ad-hoc interventions in more vulnerable cities may prove helpful in containing and reducing the impact of future pandemics.

Bayesian nonparametric inference for heterogeneously mixing infectious disease models.

SignificanceMathematical models of infectious disease transmission continue to play a vital role in understanding, mitigating, and preventing outbreaks. The vast majority of epidemic models in the literature are parametric, meaning that they contain inherent assumptions about how transmission occurs in a population. However, such assumptions can be lacking in appropriate biological or epidemiological justification and in consequence lead to erroneous scientific conclusions and misleading predictions. We propose a flexible Bayesian nonparametric framework that avoids the need to make strict model assumptions about the infection process and enables a far more data-driven modeling approach for inferring the mechanisms governing transmission. We use our methods to enhance our understanding of the transmission mechanisms of the 2001 UK foot and mouth disease outbreak.

Risks of Infectious Diseases in Newborns Exposed to Alternative Perinatal Practices.

The purpose of this report is to educate providers about the risk of infectious diseases associated with emerging alternative peripartum and neonatal practices. This report will provide information pediatricians may use to counsel families before birth and to appropriately evaluate and treat neonates who have been exposed to these practices.

Phlebotomine sand flies (Diptera: Psychodidae) of the Maghreb region: A systematic review of distribution, morphology, and role in the transmission of the pathogens.

BACKGROUND: Phlebotomine sand flies (Diptera: Psychodidae) are important vectors of various human and animal pathogens such as Bartonella bacilliformis, Phlebovirus, and parasitic protozoa of the genus Leishmania, causative agent of leishmaniases that account among most significant vector-borne diseases. The Maghreb countries Mauritania, Morocco, Algeria, Tunisia, and Libya occupy a vast area of North Africa and belong to most affected regions by these diseases. Locally varying climatic and ecological conditions support diverse sand fly fauna that includes many proven or suspected vectors. The aim of this review is to summarize often fragmented information and to provide an updated list of sand fly species of the Maghreb region with illustration of species-specific morphological features and maps of their reported distribution. MATERIALS AND METHODS: The literature search focused on scholar databases to review information on the sand fly species distribution and their role in the disease transmissions in Mauritania, Morocco, Algeria, Tunisia, and Libya, surveying sources from the period between 1900 and 2020. Reported distribution of each species was collated using Google Earth, and distribution maps were drawn using ArcGIS software. Morphological illustrations were compiled from various published sources. RESULTS AND CONCLUSIONS: In total, 32 species of the genera Phlebotomus (Ph.) and Sergentomyia (Se.) were reported in the Maghreb region (15 from Libya, 18 from Tunisia, 23 from Morocco, 24 from Algeria, and 9 from Mauritania). Phlebotomus mariae and Se. africana subsp. asiatica were recorded only in Morocco, Ph. mascitti, Se. hirtus, and Se. tiberiadis only in Algeria, whereas Ph. duboscqi, Se. dubia, Se. africana africana, Se. lesleyae, Se. magna, and Se. freetownensis were reported only from Mauritania. Our review has updated and summarized the geographic distribution of 26 species reported so far in Morocco, Algeria, Tunisia, and Libya, excluding Mauritania from a detailed analysis due to the unavailability of accurate distribution data. In addition, morphological differences important for species identification are summarized with particular attention to closely related species such as Ph. papatasi and Ph. bergeroti, Ph. chabaudi, and Ph. riouxi, and Se. christophersi and Se. clydei.

Ramadan is not associated with increased infection risk in Pakistani and Bangladeshi populations: Findings from controlled interrupted time series analysis of UK primary care data.

BACKGROUND: The effect of fasting on immunity is unclear. Prolonged fasting is thought to increase the risk of infection due to dehydration. This study describes antibiotic prescribing patterns before, during, and after Ramadan in a primary care setting within the Pakistani and Bangladeshi populations in the UK, most of whom are Muslims, compared to those who do not observe Ramadan. METHOD: Retrospective controlled interrupted time series analysis of electronic health record data from primary care practices. The study consists of two groups: Pakistanis/Bangladeshis and white populations. For each group, we constructed a series of aggregated, daily prescription data from 2007 to 2017 for the 30 days preceding, during, and after Ramadan, respectively. FINDINGS: Controlling for the rate in the white population, there was no evidence of increased antibiotic prescription in the Pakistani/Bangladeshi population during Ramadan, as compared to before Ramadan (IRR: 0.994; 95% CI: 0.988-1.001, p = 0.082) or after Ramadan (IRR: 1.006; 95% CI: 0.999-1.013, p = 0.082). INTERPRETATION: In this large, population-based study, we did not find any evidence to suggest that fasting was associated with an increased susceptibility to infection.

Evaluation of Aids and Hepatitis-B knowledge and job satisfaction among hairdressers and barbers in Turkey

Blood-borne viruses, includingthe human immunodeficiency virus and hepatitis B virus, have certain common epidemiological characteristics and these viruses infect millions of people worldwide. This study aimed to determine the job satisfaction and the level of knowledge and practices regarding infectious diseases of employees working as hairdressers and barbers.This descriptive and cross-sectional study comprised 1200 hairdressers and barbers. The study sample comprised 628 people who consented to participate in the study. The mean age of the participants who participated in the study was 28, 13 ± 6. 9 years. The mean job satisfaction score of the participants was 3.85 ± 0.58. The job satisfaction score was found to be higher among those with sufficient knowledge of hepatitis B (p < 0.005). Employees should be provided performance trainings to achieve job satisfaction. It is recommended that employees be encouraged to wear gloves and gowns to protect their health and prevent contamination.

VEuPathDB: the eukaryotic pathogen, vector and host bioinformatics resource center.

The Eukaryotic Pathogen, Vector and Host Informatics Resource (VEuPathDB, https://veupathdb.org) represents the 2019 merger of VectorBase with the EuPathDB projects. As a Bioinformatics Resource Center funded by the National Institutes of Health, with additional support from the Welllcome Trust, VEuPathDB supports >500 organisms comprising invertebrate vectors, eukaryotic pathogens (protists and fungi) and relevant free-living or non-pathogenic species or hosts. Designed to empower researchers with access to Omics data and bioinformatic analyses, VEuPathDB projects integrate >1700 pre-analysed datasets (and associated metadata) with advanced search capabilities, visualizations, and analysis tools in a graphic interface. Diverse data types are analysed with standardized workflows including an in-house OrthoMCL algorithm for predicting orthology. Comparisons are easily made across datasets, data types and organisms in this unique data mining platform. A new site-wide search facilitates access for both experienced and novice users. Upgraded infrastructure and workflows support numerous updates to the web interface, tools, searches and strategies, and Galaxy workspace where users can privately analyse their own data. Forthcoming upgrades include cloud-ready application architecture, expanded support for the Galaxy workspace, tools for interrogating host-pathogen interactions, and improved interactions with affiliated databases (ClinEpiDB, MicrobiomeDB) and other scientific resources, and increased interoperability with the Bacterial & Viral BRC.

Measles resurgence in Brazil: analysis of the 2019 epidemic in the state of São Paulo / Ressurgimento do sarampo no Brasil: análise da epidemia de 2019 no estado de São Paulo

ABSTRACT OBJECTIVE To analyze the epidemiological profile of cases and the pattern of spatial diffusion of the largest measles epidemic in Brazil that occurred in the post-elimination period in the state of São Paulo. METHOD A cross-sectional study based on confirmed measles cases in 2019. Bivariate analysis was performed for socioeconomic, clinical, and epidemiological variables, according to prior vaccination and hospitalization, combined with an analysis of spatial diffusion of cases using the Inverse Distance Weighting (IDW) method. RESULTS Of the 15,598 confirmed cases, 2,039 were hospitalized and 17 progressed to death. The epidemic peak occurred in epidemiological week 33, after confirmation of the first case, in the epidemiological week 6. Most cases were male (52.1%), aged between 18 and 29 years (38.7%), identified as whites (70%). Young adults (39.7%) and children under five years (32.8%) were the most affected age groups. A higher proportion of previous vaccination was observed in whites as compared to Blacks, browns, yellows and indigenous people (p < 0.001), as well as in the most educated group compared to the other categories (p < 0.001). The risk of hospitalization was higher in children than in the older age group (RI = 2.19; 95%CI: 1.66-2.88), as well as in the unvaccinated than in the vaccinated (RI = 1.59; 95%CI: 1.45-1.75). The pattern of diffusion by contiguity combined with diffusion by relocation followed the urban hierarchy of the main cities' regions of influence. CONCLUSION In addition to routine vaccination in children, the findings indicate the need for immunization campaigns for young adults. In addition, studies that seek to investigate the occurrence of clusters of vulnerable populations, prone to lower vaccination coverage, are essential to broaden the understanding of the dynamics of transmission and, thus, reorienting control strategies that ensure disease elimination.

RESUMO OBJETIVO Analisar o perfil epidemiológico dos casos e o padrão de difusão espacial da maior epidemia de sarampo do Brasil ocorrida no período pós-eliminação, no estado de São Paulo. MÉTODO Estudo transversal, baseado em casos confirmados de sarampo em 2019. Foi conduzida análise bivariada das variáveis socioeconômicas, clínicas e epidemiológicas, segundo vacinação prévia e ocorrência de hospitalização, combinada a uma análise de difusão espacial dos casos por meio da metodologia de interpolação pela ponderação do inverso da distância. RESULTADOS Dos 15.598 casos confirmados, 2.039 foram hospitalizados e 17 evoluíram para o óbito. O pico epidêmico ocorreu na semana epidemiológica 33, após a confirmação do primeiro caso, na semana epidemiológica 6. A maioria dos casos era homem (52,1%), com idade entre 18 e 29 anos (38,7%), identificados como brancos (70%). Adultos jovens (39,7%) e menores de cinco anos (32,8%) foram as faixas etárias mais acometidas. Observou-se maior proporção de vacinação prévia em brancos, quando comparados a pretos, pardos, amarelos e indígenas (p < 0,001), assim como no grupo mais escolarizado, quando comparado às demais categorias (p < 0,001). O risco de hospitalização foi maior em crianças, quando comparado à faixa etária mais idosa (RI = 2,19; IC95% 1,66-2,88), assim como entre não vacinados, quando comparado a vacinados (RI = 1,59; IC95% 1,45-1,75). O padrão de difusão por contiguidade combinado à difusão por realocação seguiu a hierarquia urbana das regiões de influência das principais cidades. CONCLUSÃO Além da vacinação de rotina em crianças, os achados indicam a necessidade de campanhas de imunização de adultos jovens. Adicionalmente, estudos que busquem investigar a ocorrência de clusters de populações vulneráveis, propensas a menor cobertura de vacinação, são essenciais para ampliar a compreensão sobre a dinâmica de transmissão da doença e, assim, reorientar estratégias de controle que garantam a eliminação da doença.

Revealing mechanisms of infectious disease spread through empirical contact networks.

The spread of pathogens fundamentally depends on the underlying contacts between individuals. Modeling the dynamics of infectious disease spread through contact networks, however, can be challenging due to limited knowledge of how an infectious disease spreads and its transmission rate. We developed a novel statistical tool, INoDS (Identifying contact Networks of infectious Disease Spread) that estimates the transmission rate of an infectious disease outbreak, establishes epidemiological relevance of a contact network in explaining the observed pattern of infectious disease spread and enables model comparison between different contact network hypotheses. We show that our tool is robust to incomplete data and can be easily applied to datasets where infection timings of individuals are unknown. We tested the reliability of INoDS using simulation experiments of disease spread on a synthetic contact network and find that it is robust to incomplete data and is reliable under different settings of network dynamics and disease contagiousness compared with previous approaches. We demonstrate the applicability of our method in two host-pathogen systems: Crithidia bombi in bumblebee colonies and Salmonella in wild Australian sleepy lizard populations. INoDS thus provides a novel and reliable statistical tool for identifying transmission pathways of infectious disease spread. In addition, application of INoDS extends to understanding the spread of novel or emerging infectious disease, an alternative approach to laboratory transmission experiments, and overcoming common data-collection constraints.

When and why direct transmission models can be used for environmentally persistent pathogens.

Variants of the susceptible-infected-removed (SIR) model of Kermack & McKendrick (1927) enjoy wide application in epidemiology, offering simple yet powerful inferential and predictive tools in the study of diverse infectious diseases across human, animal and plant populations. Direct transmission models (DTM) are a subset of these that treat the processes of disease transmission as comprising a series of discrete instantaneous events. Infections transmitted indirectly by persistent environmental pathogens, however, are examples where a DTM description might fail and are perhaps better described by models that comprise explicit environmental transmission routes, so-called environmental transmission models (ETM). In this paper we discuss the stochastic susceptible-exposed-infected-removed (SEIR) DTM and susceptible-exposed-infected-removed-pathogen (SEIR-P) ETM and we show that the former is the timescale separation limit of the latter, with ETM host-disease dynamics increasingly resembling those of a DTM when the pathogen's characteristic timescale is shortened, relative to that of the host population. Using graphical posterior predictive checks (GPPC), we investigate the validity of the SEIR model when fitted to simulated SEIR-P host infection and removal times. Such analyses demonstrate how, in many cases, the SEIR model is robust to departure from direct transmission. Finally, we present a case study of white spot disease (WSD) in penaeid shrimp with rates of environmental transmission and pathogen decay (SEIR-P model parameters) estimated using published results of experiments. Using SEIR and SEIR-P simulations of a hypothetical WSD outbreak management scenario, we demonstrate how relative shortening of the pathogen timescale comes about in practice. With atttempts to remove diseased shrimp from the population every 24h, we see SEIR and SEIR-P model outputs closely conincide. However, when removals are 6-hourly, the two models' mean outputs diverge, with distinct predictions of outbreak size and duration.

Individual's daily behaviour and intergenerational mixing in different social contexts of Kenya.

We investigated contact patterns in diverse social contexts in Kenya and the daily behaviours that may play a pivotal role in infection transmission to the most vulnerable leveraging novel data from a 2-day survey on social contacts and time use (TU) from a sample of 1407 individuals (for a total of 2705 person days) from rural, urban formal, and informal settings. We used TU data to build six profiles of daily behaviour based on the main reported activities, i.e., Homestayers (71.1% of person days), Workers (9.3%), Schoolers (7.8%), or locations at increasing distance from home, i.e., Walkers (6.6%), Commuters (4.6%), Travelers (0.6%). In the rural setting, we observed higher daily contact numbers (11.56, SD 0.23) and percentages of intergenerational mixing with older adults (7.5% of contacts reported by those younger than 60 years vs. less than 4% in the urban settings). Overall, intergenerational mixing with older adults was higher for Walkers (7.3% of their reported contacts), Commuters (8.7%), and Homestayers (5.1%) than for Workers (1.5%) or Schoolers (3.6%). These results could be instrumental in defining effective interventions that acknowledge the heterogeneity in social contexts and daily routines, either in Kenya or other demographically and culturally similar sub-Saharan African settings.

Network percolation reveals adaptive bridges of the mobility network response to COVID-19.

Human mobility is crucial to understand the transmission pattern of COVID-19 on spatially embedded geographic networks. This pattern seems unpredictable, and the propagation appears unstoppable, resulting in over 350,000 death tolls in the U.S. by the end of 2020. Here, we create the spatiotemporal inter-county mobility network using 10 TB (Terabytes) trajectory data of 30 million smart devices in the U.S. in the first six months of 2020. We investigate the bond percolation process by removing the weakly connected edges. As we increase the threshold, the mobility network nodes become less interconnected and thus experience surprisingly abrupt phase transitions. Despite the complex behaviors of the mobility network, we devised a novel approach to identify a small, manageable set of recurrent critical bridges, connecting the giant component and the second-largest component. These adaptive links, located across the United States, played a key role as valves connecting components in divisions and regions during the pandemic. Beyond, our numerical results unveil that network characteristics determine the critical thresholds and the bridge locations. The findings provide new insights into managing and controlling the connectivity of mobility networks during unprecedented disruptions. The work can also potentially offer practical future infectious diseases both globally and locally.

Changes in notifiable infectious disease incidence in China during the COVID-19 pandemic.

Nationwide nonpharmaceutical interventions (NPIs) have been effective at mitigating the spread of the novel coronavirus disease (COVID-19), but their broad impact on other diseases remains under-investigated. Here we report an ecological analysis comparing the incidence of 31 major notifiable infectious diseases in China in 2020 to the average level during 2014-2019, controlling for temporal phases defined by NPI intensity levels. Respiratory diseases and gastrointestinal or enteroviral diseases declined more than sexually transmitted or bloodborne diseases and vector-borne or zoonotic diseases. Early pandemic phases with more stringent NPIs were associated with greater reductions in disease incidence. Non-respiratory diseases, such as hand, foot and mouth disease, rebounded substantially towards the end of the year 2020 as the NPIs were relaxed. Statistical modeling analyses confirm that strong NPIs were associated with a broad mitigation effect on communicable diseases, but resurgence of non-respiratory diseases should be expected when the NPIs, especially restrictions of human movement and gathering, become less stringent.

Switchover phenomenon induced by epidemic seeding on geometric networks.

It is a fundamental question in disease modeling how the initial seeding of an epidemic, spreading over a network, determines its final outcome. One important goal has been to find the seed configuration, which infects the most individuals. Although the identified optimal configurations give insight into how the initial state affects the outcome of an epidemic, they are unlikely to occur in real life. In this paper we identify two important seeding scenarios, both motivated by historical data, that reveal a complex phenomenon. In one scenario, the seeds are concentrated on the central nodes of a network, while in the second one, they are spread uniformly in the population. Comparing the final size of the epidemic started from these two initial conditions through data-driven and synthetic simulations on real and modeled geometric metapopulation networks, we find evidence for a switchover phenomenon: When the basic reproduction number [Formula: see text] is close to its critical value, more individuals become infected in the first seeding scenario, but for larger values of [Formula: see text], the second scenario is more dangerous. We find that the switchover phenomenon is amplified by the geometric nature of the underlying network and confirm our results via mathematically rigorous proofs, by mapping the network epidemic processes to bond percolation. Our results expand on the previous finding that, in the case of a single seed, the first scenario is always more dangerous and further our understanding of why the sizes of consecutive waves of a pandemic can differ even if their epidemic characters are similar.