Seasonal variations in social contact patterns in a rural population in north India: Implications for pandemic control.

Social contact mixing patterns are critical to model the transmission of communicable diseases, and have been employed to model disease outbreaks including COVID-19. Nonetheless, there is a paucity of studies on contact mixing in low and middle-income countries such as India. Furthermore, mathematical models of disease outbreaks do not account for the temporal nature of social contacts. We conducted a longitudinal study of social contacts in rural north India across three seasons and analysed the temporal differences in contact patterns. A contact diary survey was performed across three seasons from October 2015-16, in which participants were queried on the number, duration, and characteristics of contacts that occurred on the previous day. A total of 8,421 responses from 3,052 respondents (49% females) recorded characteristics of 180,073 contacts. Respondents reported a significantly higher number and duration of contacts in the winter, followed by the summer and the monsoon season (Nemenyi post-hoc, p<0.001). Participants aged 0-9 years and 10-19 years of age reported the highest median number of contacts (16 (IQR 12-21), 17 (IQR 13-24) respectively) and were found to have the highest node centrality in the social network of the region (pageranks = 0.20, 0.17). A large proportion (>80%) of contacts that were reported in schools or on public transport involved physical contact. To the best of our knowledge, our study is the first from India to show that contact mixing patterns vary by the time of the year and provides useful implications for pandemic control. We compared the differences in the number, duration and location of contacts by age-group and gender, and studied the impact of the season, age-group, employment and day of the week on the number and duration of contacts using multivariate negative binomial regression. We created a social network to further understand the age and gender-specific contact patterns, and used the contact matrices in each season to parameterise a nine-compartment agent-based model for simulating a COVID-19 epidemic in each season. Our results can be used to parameterize more accurate mathematical models for prediction of epidemiological trends of infections in rural India.

Transport of synaptic vesicles is modulated by vesicular reversals and stationary cargo clusters.

Stationary clusters of vesicles are a prominent feature of axonal transport, but little is known about their physiological and functional relevance to axonal transport. Here, we investigated the role of vesicle motility characteristics in modulating the formation and lifetimes of such stationary clusters, and their effect on cargo flow. We developed a simulation model describing key features of axonal cargo transport, benchmarking the model against experiments in the posterior lateral mechanosensory neurons of Caenorhabditis elegans. Our simulations included multiple microtubule tracks and varied cargo motion states, and account for dynamic cargo-cargo interactions. Our model also incorporates static obstacles to vesicle transport in the form of microtubule ends, stalled vesicles and stationary mitochondria. We demonstrate, both in simulations and in an experimental system, that a reduction in reversal rates is associated with a higher proportion of long-lived stationary vesicle clusters and reduced net anterograde transport. Our simulations support the view that stationary clusters function as dynamic reservoirs of cargo vesicles, and reversals aid cargo in navigating obstacles and regulate cargo transport by modulating the proportion of stationary vesicle clusters along the neuronal process.

Effect of hybrid immunity, school reopening, and the Omicron variant on the trajectory of the COVID-19 epidemic in India: a modelling study.

Background: The course of the COVID-19 pandemic has been driven by several dynamic behavioral, immunological, and viral factors. We used mathematical modeling to explore how the concurrent reopening of schools, increasing levels of hybrid immunity, and the emergence of the Omicron variant affected the trajectory of the pandemic in India, using Andhra Pradesh (pop: 53 million) as an exemplar Indian state. Methods: We constructed an age- and contact-structured compartmental model that allows for individuals to proceed through various states depending on whether they have received zero, one, or two doses of the COVID-19 vaccine. We calibrated our model using results from another model (i.e., INDSCI-SIM) as well as available context-specific serosurvey data. The introduction of the Omicron variant is modelled alongside protection gained from hybrid immunity. We predict disease dynamics in the background of hybrid immunity coming from infections and an ongoing vaccination program, given prior levels of seropositivity from earlier waves of infection. We describe the consequences of school reopening on cases across different age-bands, as well as the impact of the Omicron (BA.2) variant. Findings: We show the existence of an epidemic peak in India that is strongly related to the value of background seroprevalence. As expected, because children were not vaccinated in India, re-opening schools increases the number of cases in children more than in adults, although in all scenarios, the peak number of active hospitalizations was never greater than 0.45 times the corresponding peak in the Delta wave before schools were reopened. We varied the level of infection induced seropositivity in our model and found the height of the peak associated with schools reopening reduced as background infection-induced seropositivity increased from 20% to 40%. At reported values of seropositivity of 64% from representative surveys done in India, no discernible peak was observed. We also explored counterfactual scenarios regarding the effect of vaccination on hybrid immunity. We found that in the absence of vaccination, even at high levels of seroprevalence (>60%), the emergence of the Omicron variant would have resulted in a large rise in cases across all age bands by as much as 1.8 times. We conclude that the presence of high levels of hybrid immunity resulted in fewer cases in the Omicron wave than in the Delta wave. Interpretation: In India, decreasing prevalence of immunologically naïve individuals of all ages was associated with fewer cases reported once schools were reopened. In addition, hybrid immunity, together with the lower intrinsic severity of disease associated with the Omicron variant, contributed to low reported COVID-19 hospitalizations and deaths. Funding: World Health Organization, Mphasis.

The interplay of active and passive mechanisms in slow axonal transport.

A combination of intermittent active movement of transient aggregates and a paused state that intervenes between periods of active transport has been proposed to underlie the slow, directed transport of soluble proteins in axons. A component of passive diffusion in the axoplasm may also contribute to slow axonal transport, although quantitative estimates of the relative contributions of diffusive and active movement in the slow transport of a soluble protein, and in particular how they might vary across developmental stages, are lacking. Here, we propose and study a model for slow axonal transport, addressing data from bleach recovery measurements on a small, soluble, protein, choline acetyltransferase, in thin axons of the lateral chordotonal (lch5) sensory neurons of Drosophila. Choline acetyltransferase is mainly present in soluble form in the axon and catalyzes the acetylation of choline at the synapse. It does not form particulate structures in axons and moves at rates characteristic of slow component b (≈ 1-10 mm/day or 0.01-0.1 µm/s). Using our model, which incorporates active transport with paused and/or diffusive states, we predict bleach recovery, transport rates, and cargo trajectories obtained through kymographs, comparing these with experimental observations at different developmental stages. We show that changes in the diffusive fraction of cargo during these developmental stages dominate bleach recovery and that a combination of active motion with a paused state alone cannot reproduce the data. We compared predictions of the model with results from photoactivation experiments. The importance of the diffusive state in reproducing the bleach recovery signal in the slow axonal transport of small soluble proteins is our central result.

Modelling the first wave of COVID-19 in India.

Estimating the burden of COVID-19 in India is difficult because the extent to which cases and deaths have been undercounted is hard to assess. Here, we use a 9-component, age-stratified, contact-structured epidemiological compartmental model, which we call the INDSCI-SIM model, to analyse the first wave of COVID-19 spread in India. We use INDSCI-SIM, together with Bayesian methods, to obtain optimal fits to daily reported cases and deaths across the span of the first wave of the Indian pandemic, over the period Jan 30, 2020 to Feb 15, 2021. We account for lock-downs and other non-pharmaceutical interventions (NPIs), an overall increase in testing as a function of time, the under-counting of cases and deaths, and a range of age-specific infection-fatality ratios. We first use our model to describe data from all individual districts of the state of Karnataka, benchmarking our calculations using data from serological surveys. We then extend this approach to aggregated data for Karnataka state. We model the progress of the pandemic across the cities of Delhi, Mumbai, Pune, Bengaluru and Chennai, and then for India as a whole. We estimate that deaths were undercounted by a factor between 2 and 5 across the span of the first wave, converging on 2.2 as a representative multiplier that accounts for the urban-rural gradient. We also estimate an overall under-counting of cases by a factor of between 20 and 25 towards the end of the first wave. Our estimates of the infection fatality ratio (IFR) are in the range 0.05-0.15, broadly consistent with previous estimates but substantially lower than values that have been estimated for other LMIC countries. We find that approximately 35% of India had been infected overall by the end of the first wave, results broadly consistent with those from serosurveys. These results contribute to the understanding of the long-term trajectory of COVID-19 in India.

Exploring the thermal limits of malaria transmission in the western Himalaya.

Environmental temperature is a key driver of malaria transmission dynamics. Using detailed temperature records from four sites: low elevation (1800), mid elevation (2200 m), and high elevation (2600-3200 m) in the western Himalaya, we model how temperature regulates parasite development rate (the inverse of the extrinsic incubation period, EIP) in the wild. Using a Briére parametrization of the EIP, combined with Bayesian parameter inference, we study the thermal limits of transmission for avian (Plasmodium relictum) and human Plasmodium parasites (P. vivax and P. falciparum) as well as for two malaria-like avian parasites, Haemoproteus and Leucocytozoon. We demonstrate that temperature conditions can substantially alter the incubation period of parasites at high elevation sites (2600-3200 m) leading to restricted parasite development or long transmission windows. The thermal limits (optimal temperature) for Plasmodium parasites were 15.62-34.92°C (30.04°C) for P. falciparum, 13.51-34.08°C (29.02°C) for P. vivax, 12.56-34.46°C (29.16°C) for P. relictum and for two malaria-like parasites, 12.01-29.48°C (25.16°C) for Haemoproteus spp. and 11.92-29.95°C (25.51°C) for Leucocytozoon spp. We then compare estimates of EIP based on measures of mean temperature versus hourly temperatures to show that EIP days vary in cold versus warm environments. We found that human Plasmodium parasites experience a limited transmission window at 2600 m. In contrast, for avian Plasmodium transmission was not possible between September and March at 2600 m. In addition, temperature conditions suitable for both Haemoproteus and Leucocytozoon transmission were obtained from June to August and in April, at 2600 m. Finally, we use temperature projections from a suite of climate models to predict that by 2040, high elevation sites (~2600 m) will have a temperature range conducive for malaria transmission, albeit with a limited transmission window. Our study highlights the importance of accounting for fine-scale thermal effects in the expansion of the range of the malaria parasite with global climate change.

Cell adhesion strength and tractions are mechano-diagnostic features of cellular invasiveness.

The adhesion of cells to substrates occurs via integrin clustering and binding to the actin cytoskeleton. Oncogenes modify anchorage-dependent mechanisms in cells during cancer progression. Fluid shear devices provide a label-free way to characterize cell-substrate interactions and heterogeneities in cell populations. We quantified the critical adhesion strengths of MCF-7, MDAMB-231, A549, HPL1D, HeLa, and NIH3T3 cells using a custom fluid shear device. The detachment response was sigmoidal for each cell type. A549 and MDAMB-231 cells had significantly lower critical adhesion strengths (τ50) than their non-invasive counterparts, HPL1D and MCF-7. Detachment dynamics inversely correlated with cell invasion potentials. A theoretical model, based on τ50 values and the distribution of cell areas on substrates, provided good fits to results from de-adhesion experiments. Quantification of cell tractions, using the Reg-FTTC method on 10 kPa polyacrylamide gels, showed highest values for invasive, MDAMB-231 and A549, cells compared to non-invasive cells. Immunofluorescence studies show differences in vinculin distributions; non-invasive cells have distinct vinculin puncta, whereas invasive cells have more dispersed distributions. The cytoskeleton in non-invasive cells was devoid of well-developed stress fibers, and had thicker cortical actin bundles in the boundary. Fluorescence intensity of actin was significantly lower in invasive cells as compared to non invasive cells. These correlations in adhesion strengths and traction stresses with cell invasiveness may be useful in cancer diagnostics and other pathologies featuring mis-regulation in adhesion.

Phototaxis in Cyanobacteria: From Mutants to Models of Collective Behavior.

Cyanobacteria rely on photosynthesis, and thus have evolved complex responses to light. These include phototaxis, the ability of cells to sense light direction and move towards or away from it. Analysis of mutants has demonstrated that phototaxis requires the coordination of multiple photoreceptors and signal transduction networks. The output of these networks is relayed to type IV pili (T4P) that attach to and exert forces on surfaces or other neighboring cells to drive "twitching" or "gliding" motility. This, along with the extrusion of polysaccharides or "slime" by cells, facilitates the emergence of group behavior. We evaluate recent models that describe the emergence of collective colony-scale behavior from the responses of individual, interacting cells. We highlight the advantages of "active matter" approaches in the study of bacterial communities, discussing key differences between emergent behavior in cyanobacterial phototaxis and similar behavior in chemotaxis or quorum sensing.

Optimizing testing for COVID-19 in India.

COVID-19 testing across India uses a mix of two types of tests. Rapid Antigen Tests (RATs) are relatively inexpensive point-of-care lateral-flow-assay tests, but they are also less sensitive. The reverse-transcriptase polymerase-chain-reaction (RT-PCR) test has close to 100% sensitivity and specificity in a laboratory setting, but delays in returning results, as well as increased costs relative to RATs, may vitiate this advantage. India-wide, about 49% of COVID-19 tests are RATs, but some Indian states, including the large states of Uttar Pradesh (pop. 227.9 million) and Bihar (pop. 121.3 million) use a much higher proportion of such tests. Here we show, using simulations based on epidemiological network models, that the judicious use of RATs can yield epidemiological outcomes comparable to those obtained through RT-PCR-based testing and isolation of positives, provided a few conditions are met. These are (a) that RAT test sensitivity is not too low, (b) that a reasonably large fraction of the population, of order 0.5% per day, can be tested, (c) that those testing positive are isolated for a sufficient duration, and that (d) testing is accompanied by other non-pharmaceutical interventions for increased effectiveness. We assess optimal testing regimes, taking into account test sensitivity and specificity, background seroprevalence and current test pricing. We find, surprisingly, that even 100% RAT test regimes should be acceptable, from both an epidemiological as well as a economic standpoint, provided the conditions outlined above are met.

Comparing COVID-19 vaccine allocation strategies in India: A mathematical modelling study.

BACKGROUND: The development and widespread use of an effective SARS-CoV-2 vaccine could prevent substantial morbidity and mortality associated with COVID-19 and mitigate the secondary effects associated with non-pharmaceutical interventions. METHODS: We used an age-structured, expanded SEIR model with social contact matrices to assess age-specific vaccine allocation strategies in India. We used state-specific age structures and disease transmission coefficients estimated from confirmed incident cases of COVID-19 between 1 July and 31 August 2020. Simulations were used to investigate the relative reduction in mortality and morbidity of vaccine allocation strategies based on prioritizing different age groups, and the interactions of these strategies with concurrent non-pharmaceutical interventions. Given the uncertainty associated with COVID-19 vaccine development, we varied vaccine characteristics in the modelling simulations. RESULTS: Prioritizing COVID-19 vaccine allocation for older populations (i.e., >60 years) led to the greatest relative reduction in deaths, regardless of vaccine efficacy, control measures, rollout speed, or immunity dynamics. Preferential vaccination of this group often produced relatively higher total symptomatic infections and more pronounced estimates of peak incidence than other assessed strategies. Vaccine efficacy, immunity type, target coverage, and rollout speed significantly influenced overall strategy effectiveness, with the time taken to reach target coverage significantly affecting the relative mortality benefit comparative to no vaccination. CONCLUSIONS: Our findings support global recommendations to prioritize COVID-19 vaccine allocation for older age groups. Relative differences between allocation strategies were reduced as the speed of vaccine rollout was increased. Optimal vaccine allocation strategies will depend on vaccine characteristics, strength of concurrent non-pharmaceutical interventions, and region-specific goals.

Altered kinetics of circulating progenitor cells in cardiopulmonary bypass (CPB) associated vasoplegic patients: A pilot study.

Vasoplegia observed post cardiopulmonary bypass (CPB) is associated with substantial morbidity, multiple organ failure and mortality. Circulating counts of hematopoietic stem cells (HSCs) and endothelial progenitor cells (EPC) are potential markers of neo-vascularization and vascular repair. However, the significance of changes in the circulating levels of these progenitors in perioperative CPB, and their association with post-CPB vasoplegia, are currently unexplored. We enumerated HSC and EPC counts, via flow cytometry, at different time-points during CPB in 19 individuals who underwent elective cardiac surgery. These 19 individuals were categorized into two groups based on severity of post-operative vasoplegia, a clinically insignificant vasoplegic Group 1 (G1) and a clinically significant vasoplegic Group 2 (G2). Differential changes in progenitor cell counts during different stages of surgery were compared across these two groups. Machine-learning classifiers (logistic regression and gradient boosting) were employed to determine if differential changes in progenitor counts could aid the classification of individuals into these groups. Enumerating progenitor cells revealed an early and significant increase in the circulating counts of CD34+ and CD34+CD133+ hematopoietic stem cells (HSC) in G1 individuals, while these counts were attenuated in G2 individuals. Additionally, EPCs (CD34+VEGFR2+) were lower in G2 individuals compared to G1. Gradient boosting outperformed logistic regression in assessing the vasoplegia grouping based on the fold change in circulating CD 34+ levels. Our findings indicate that a lack of early response of CD34+ cells and CD34+CD133+ HSCs might serve as an early marker for development of clinically significant vasoplegia after CPB.

Chromatin as an active polymeric material.

The patterns of the large-scale spatial organization of chromatin in interphase human somatic cells are not random. Such patterns include the radial separation of euchromatin and heterochromatin, the territorial organization of individual chromosomes, the non-random locations of chromosome territories and the differential positioning of the two X chromosomes in female cells. These features of large-scale nuclear architecture follow naturally from the hypothesis that ATP-consuming non-equilibrium processes associated with highly transcribed regions of chromosomes are a source of 'active' forces. These forces are in excess of those that arise from Brownian motion. Simulations of model chromosomes that incorporate such activity recapitulate these features. In addition, they reproduce many other aspects of the spatial organization of chromatin at large scales that are known from experiments. Our results, reviewed here, suggest that the distribution of transcriptional activity across chromosomes underlies many aspects of large-scale nuclear architecture that were hitherto believed to be unrelated.

Information integration and collective motility in phototactic cyanobacteria.

Cells in microbial colonies integrate information across multiple spatial and temporal scales while sensing environmental cues. A number of photosynthetic cyanobacteria respond in a directional manner to incident light, resulting in the phototaxis of individual cells. Colonies of such bacteria exhibit large-scale changes in morphology, arising from cell-cell interactions, during phototaxis. These interactions occur through type IV pili-mediated physical contacts between cells, as well as through the secretion of complex polysaccharides ('slime') that facilitates cell motion. Here, we describe a computational model for such collective behaviour in colonies of the cyanobacterium Synechocystis. The model is designed to replicate observations from recent experiments on the emergent response of the colonies to varied light regimes. It predicts the complex colony morphologies that arise as a result. We ask if changes in colony morphology during phototaxis can be used to infer if cells integrate information from multiple light sources simultaneously, or respond to these light sources separately at each instant of time. We find that these two scenarios cannot be distinguished from the shapes of colonies alone. However, we show that tracking the trajectories of individual cyanobacteria provides a way of determining their mode of response. Our model allows us to address the emergent nature of this class of collective bacterial motion, linking individual cell response to the dynamics of colony shape.

Disorder-induced enhancement of local hexatic correlations in two-dimensional fluids.

Quenched disorder affects translational and orientational correlations in two-dimensional interacting particle systems. Such disorder always suppresses orientational order in crystalline states. Surprisingly, in fluid phases of particles interacting with a power-law repulsive interaction, increasing the strength of a quenched Gaussian random pinning potential appears to enhance hexatic order locally. We propose that nearby pairs of pinned particles lock in the relative orientation of neighbours around them, propagating hexatic orientational order across larger distances than in the unpinned fluid. We test this idea using Monte Carlo simulations of interacting particles in their fluid phase in two dimensions, where two of the particles are constrained to be permanently pinned at a fixed distance from each other. We use Voronoi tesselations of instantaneous particle configurations to demonstrate that these pinned particles create hexatic neighbourhoods that can extend well beyond the range of their separation. This structuring is enhanced when the particle density is increased and is most prominent in the vicinity of the liquid-solid transition. Testing these ideas experimentally using experiments on 2D colloidal systems should be feasible.

Nonequilibrium Biophysical Processes Influence the Large-Scale Architecture of the Cell Nucleus.

Model approaches to nuclear architecture have traditionally ignored the biophysical consequences of ATP-fueled active processes acting on chromatin. However, transcription-coupled activity is a source of stochastic forces that are substantially larger than the Brownian forces present at physiological temperatures. Here, we describe an approach to large-scale nuclear architecture in metazoans that incorporates cell-type-specific active processes. The model predicts the statistics of positional distributions, shapes, and overlaps of each chromosome. Simulations of the model reproduce common organizing principles underlying large-scale nuclear architecture across human cell nuclei in interphase. These include the differential positioning of euchromatin and heterochromatin, the territorial organization of chromosomes (including both gene-density-based and size-based chromosome radial positioning schemes), the nonrandom locations of chromosome territories, and the shape statistics of individual chromosomes. We propose that the biophysical consequences of the distribution of transcriptional activity across chromosomes should be central to any chromosome positioning code.

Biophysics of Cell-Substrate Interactions Under Shear.

Cells adhere to substrates through mechanosensitive focal adhesion complexes. Measurements that probe how cells detach from substrates when they experience an applied force connect molecular-scale aspects of cell adhesion with the biophysical properties of adherent cells. Such forces can be applied through shear devices that flow fluid in a controlled manner across cells. The signaling pathways associated with focal adhesions, in particular those that involve integrins and receptor tyrosine kinases, are complex, receiving mechano-chemical feedback from the sensing of substrate stiffness as well as of external forces. This article reviews the signaling processes involved in mechanosensing and mechanotransduction during cell-substrate interactions, describing the role such signaling plays in cancer metastasis. We examine some recent progress in quantifying the strength of these interactions, describing a novel fluid shear device that allows for the visualization of the cell and its sub-cellular structures under a shear flow. We also summarize related results from a biophysical model for cellular de-adhesion induced by applied forces. Quantifying cell-substrate adhesions under shear should aid in the development of mechano-diagnostic techniques for diseases in which cell-adhesion is mis-regulated, such as cancers.

Orientational correlations in fluids with quenched disorder.

Snapshots of colloidal particles moving on disordered two-dimensional substrates can be used to extract equal-time many-body correlations in their positions. To understand the systematics of these correlations, we perform Monte Carlo simulations of a two-dimensional model fluid placed in a quenched disordered background. We use configurations generated from these simulations to compute translational and orientational two-point correlations at equal time, concentrating on correlations in local orientational order as a function of density and disorder strength. We calculate both the disorder averaged version of conventional two-point correlation functions for orientational order, as well as the disorder averaged version of a novel correlation function of time-averaged disorder-induced inhomogeneities in local orientation analogous to the Edwards-Anderson correlation function in spin systems. We demonstrate that these correlations can exhibit interesting nonmonotonic behavior in proximity to the underlying fluid-solid transition and suggest that this prediction should be experimentally accessible.