Shielding individuals at high risk of COVID-19: a micro-simulation study

Background One of the proposed interventions for mitigating COVID-19 epidemics, particularly in low-income and crisis-affected settings, is to physically isolate individuals known to be at high risk of severe disease and death due to age or co-morbidities. This intervention, known as 'shielding', could be implemented in various ways. If shielded people are grouped together in residences and isolation is imperfect, any introduction of infections within the shielding group could cause substantial mortality and thus negate the intervention's benefits. We explored the effectiveness of shielding under various modalities of implementation and considered mitigation measures to reduce its possible harms. Methods We used an individual-based mathematical model to simulate the evolution of a COVID-19 epidemic in a population of which a fraction above a given age cut-off are relocated to shielding residences, in which they have variable levels of contacts with their original household, the outside world and fellow shielding residents. We set our simulation with the context of an internally displaced persons' camp in Somaliland, for which we had recently collected data on household demographics and social mixing patterns. We compared an unmitigated epidemic with a shielding intervention accompanied by various measures to reduce the risk of virus introduction and spread within the shielding residences. We did sensitivity analyses to explore parameters such as residence size, reduction in contacts, basic reproduction number, and prior immunity in the population. Results Shielded residences are likely to be breached with infection during the outbreak. Nonetheless, shielding can be effective in preventing COVID-19 infections in the shielded population. The effectiveness of shielding is mostly affected by the size of the shielded residence, and by the degree by which contacts between shielded and unshielded individuals are reduced. Reductions in contacts between shielded individuals could further increase the effectiveness of shielding, but is only effective in larger shielded residences. Large shielded residences increase the risk of infection, unless very large reductions in contacts can be achieved. In epidemics with a lower reproduction number, the effectiveness of shielding could be negative effectiveness. Discussion Shielding could be an effective method to protect the most at-risk individuals. It should be considered where other measures cannot easily be implemented, but with attention to the epidemiological situation. Shielding should only be implemented through small to medium-sized shielding residences, with appropriate mitigation measures such as reduced contact intensity between shielded individuals and self-isolation of cases to prevent subsequent spread.

Social mixing patterns relevant to infectious diseases spread by close contact in urban Blantyre, Malawi.

Introduction: Understanding human mixing patterns relevant to infectious diseases spread through close contact is vital for modelling transmission dynamics and optimisation of disease control strategies. Mixing patterns in low-income countries like Malawi are not well understood. Methodology: We conducted a social mixing survey in urban Blantyre, Malawi between April and July 2021 (between the 2nd and 3rd wave of COVID-19 infections). Participants living in densely-populated neighbourhoods were randomly sampled and, if they consented, reported their physical and non-physical contacts within and outside homes lasting at least 5 minutes during the previous day. Age-specific mixing rates were calculated, and a negative binomial mixed effects model was used to estimate determinants of contact behaviour. Results: Of 1,201 individuals enrolled, 702 (58.5%) were female, the median age was 15 years (interquartile range [IQR] 5-32) and 127 (10.6%) were HIV-positive. On average, participants reported 10.3 contacts per day (range: 1-25). Mixing patterns were highly age-assortative, particularly those within the community and with skin-to-skin contact. Adults aged 20-49y reported the most contacts (median:11, IQR: 8-15) of all age groups; 38% (95%CI: 16-63) more than infants (median: 8, IQR: 5-10), who had the least contacts. Household contact frequency increased by 3% (95%CI 2-5) per additional household member. Unemployed participants had 15% (95%CI: 9-21) fewer contacts than other adults. Among long range (>30 meters away from home) contacts, secondary school children had the largest median contact distance from home (257m, IQR 78-761). HIV-positive status in adults >18 years-old was not associated with increased contact patterns (1%, 95%CI -9-12). During this period of relatively low COVID-19 incidence in Malawi, 301 (25.1%) individuals stated that they had limited their contact with others due to COVID-19 precautions; however, their reported contacts were not fewer (8%, 95%CI 1-13). Conclusion: In urban Malawi, contact rates, are high and age-assortative, with little behavioural change due to either HIV-status or COVID-19 circulation. This highlights the limits of contact-restriction-based mitigation strategies in such settings and the need for pandemic preparedness to better understand how contact reductions can be enabled and motivated. Keywords: Social contacts, Transmission, Mixing data, Infectious disease, Malawi, Africa

Temporal changes in nutrients in a deep oligomictic lake: the role of external loads versus internal processes

The impact of climate change on stratification and mixing patterns has important effects on nutrient availability and plankton dynamics in deep lakes. We demonstrate this in a long-term study of Lake Maggiore, a deep oligomictic lake located in the subalpine lake district in Northern Italy. Studies on physical, chemical and biological features of the lake have been performed continuously since the 1980s. The lake recovered from eutrophication in response to a reduction of catchment nutrient loads and reached a stable oligotrophic status by the end of the 1990s, with average total phosphorus concentrations in the water column around 10 µg L-1. However, both reactive and total phosphorus have slightly increased since 2010, leading to a shift in the lake trophic state towards mesotrophy. The increase in phosphorus has been limited to the hypolimnetic layers, concentrations being fairly stable or decreasing in the epilimnion. Reactive silica also progressively increased in the hypolimnion, while nitrate and total nitrogen concentrations have steadily decreased in both deep and surface layers, especially in the summer period. These changes were assessed in relation to catchment loads, atmospheric deposition and climate-related variations in stratification and mixing patterns and in nutrient retention. Long-term changes in primary production, represented by chlorophyll levels, and biovolume of the main algal groups were also considered. During the eutrophication period and until the 1990s, in-lake phosphorus concentrations were tightly related to external loads; successively, phosphorus and its vertical distribution up the water column became more controlled by internal processes, in particular by stratification and mixing regime. An increase of thermal stability and a reduced frequency and intensity of deep mixing events has fostered oxygen depletion and phosphorus and silica accumulation in the hypolimnion. Another consequence of reduced deep mixing events, has been a reduction in nutrient replenishment of the upper layers at spring mixing. External loads are still the main driver of change for nitrogen compounds: the decrease in the atmospheric load of nitrogen that occurred in the Lake Maggiore area over the last decade, as an effect of reduced nitrogen emissions, has caused decreasing concentration of inorganic nitrogen in the lake. However, the phytoplankton community changes observed might also play a role in nitrogen dynamics, particularly in the nitrate minima observed during summer in recent years.

Investigating the relationship between interventions, contact patterns, and SARS-CoV-2 transmissibility

Background After a rapid upsurge of COVID-19 cases in Italy during the fall of 2020, the government introduced a three-tiered restriction system aimed at increasing physical distancing. The Ministry of Health, after periodic epidemiological risk assessments, assigned a tier to each of the 21 Italian regions and autonomous provinces (AP). It is still unclear to what extent these different measures altered mixing patterns and how quickly the population adapted their social interactions to continuous changes in restrictions. Methods and findings We conducted a survey between July 2020 and March 2021 to monitor changes in social contact patterns among individuals in the metropolitan city of Milan, Italy, which was hardly hit by the second wave of COVID-19 pandemic. The number of contacts during periods characterized by different levels of restrictions was analyzed through negative binomial regression models and age-specific contact matrices were estimated under the different tiers. Relying on the empirically estimated mixing patterns, we quantified relative changes in SARS-CoV-2 transmission potential associated with the different tiers. As tighter restrictions were implemented during the fall of 2020, a progressive reduction in the mean number of contacts recorded by study participants was observed: from 16.4% under mild restrictions (yellow tier), to 45.6% under strong restrictions (red tier). Higher restrictions levels were also found to increase the relative contribution of contacts occurring within the household. The SARS-CoV-2 reproduction number was estimated to decrease by 18.7% (95%CI: 4.6-30.8), 33.4% (95%CI: 22.7-43.2), and 50.2% (95%CI: 40.9-57.7) under the yellow, orange, and red tiers, respectively. Conclusions Our results give an important quantification of the expected contribution of different restriction levels in shaping social contacts and decreasing the transmission potential of SARS-CoV-2. These estimates can find an operational use in anticipating the effect that the implementation of these tiered restriction can have on SARS-CoV-2 reproduction number under an evolving epidemiological situation.

Adaptive data-driven age and patch mixing in contact networks with recurrent mobility

Infectious disease transmission models often stratify populations by age and geographic patches. Contact patterns between age groups and patches are key parameters in such models. Arenas et al. (2020) develop an approach to simulate contact patterns associated with recurrent mobility between patches, such as due to work, school, and other regular travel. Using their approach, mixing between patches is greater than mobility data alone would suggest, because individuals from patches A and B can form a contact if they meet in patch C. We build upon their approach to address three potential gaps that remain. First, our approach includes a distribution of contacts by age that is responsive to underlying age distribution of the mixing pool. Second, different age distributions by contact type are also maintained in our approach, such that changes to the numbers of different types of contacts are appropriately reflected in changes to the overall age mixing patterns. Finally, we introduce and distinguish between two mixing pools associated with each patch, with possible implications for the overall connectivity of the population: the home pool, in which contacts can only be formed with other individuals residing in the same patch; and the travel pool, in which contacts can be formed with some residents of, and any other visitors to the patch. We describe in detail the steps required to implement our approach, and present results of an example application.Graphical Abstract

Association between tuberculosis in men and social network structure in Kampala, Uganda

Background Globally, tuberculosis disease (TB) is more common among males than females. Recent research proposes that differences in social mixing by sex could alter infection patterns in TB. We examine evidence for two mechanisms by which social-mixing could increase men’s contact rates with TB cases. First, men could be positioned in social networks such that they contact more people or social groups. Second, preferential mixing by sex could prime men to have more exposure to TB cases. Methods We compared the networks of male and female TB cases and healthy matched controls living in Kampala, Uganda. Specifically, we estimated their positions in social networks (network distance to TB cases, degree, betweenness, and closeness) and assortativity patterns (mixing with adult men, women, and children inside and outside the household). Results The observed network consisted of 11,840 individuals. There were few differences in estimates of node position by sex. We found distinct mixing patterns by sex and TB disease status including that TB cases have proportionally more adult male contacts and fewer contacts with children. Conclusions This analysis used a network approach to study how social mixing patterns are associated with TB disease. Understanding these mechanisms may have implications for designing targeted intervention strategies in high-burden populations.

1146Assessing the uncertainty around age-mixing patterns in HIV transmission inferred from phylogenetic trees

Introduction Understand age-mixing patterns in HIV transmission is a key to design and implement HIV prevention interventions. As such, the use of phylogenetic tree seems promising since this approach is based on data from a transmission network. Methods Through a simulation study, we used transmission clusters computed from phylogenetic trees to investigate age-mixing patterns. From transmission clusters, we estimated a transmission network using pairings. We inferred measurements, which depict age-mixing patterns in transmission i.e. ‘proportions of men/women of a certain age-group paired with women/men of another age-group’, and mean, median, and standard deviation of average age difference between women/men with their respective pairs. We investigated the uncertainty around these measurements as a function of sampling coverage in different sequence missingness scenarios. Results According to the simulation set-up of age mixing in partnership, there are relationships, which are less likely and others highly likely. Explicitly, partnerships between younger men (<25 years) and older women (25 to 50 years) are less likely to happen in the sexual network, whereas partnership between younger women (<25 years) and older men (25 to 50 years) are more likely to happen as are age group relationship having intermediate magnitude in partnership. Conclusion Transmission clusters allow us to strive with more improved information regarding cross-generation transmission. It enables us to understand the importance of age mixing beyond describing the mean age difference, and that one needs to consider the variation of age differences between pairs of individuals as well as among the partners of a given individual.

A general model for the demographic signatures of the transition from pandemic emergence to endemicity

Anticipating the medium- and long-term trajectory of pathogen emergence has acquired new urgency given the ongoing COVID-19 pandemic. For many human pathogens, the burden of disease depends on age and previous exposure. Understanding the intersection between human population demography and transmission dynamics is therefore critical. Here, we develop a realistic age-structured mathematical model that integrates demography, social mixing, and immunity to establish a plausible range for future age incidence and mortality. With respect to COVID-19, we identify a plausible transition in the age structure of risks once the disease reaches seasonal endemism across a range of immunity durations and relative severity of primary versus subsequent reinfections. We train the model using diverse real-world demographies and age-structured mixing to bound expectations for changing age incidence and disease burden. The mathematical framework is flexible and can help tailor mitigation strategies in countries worldwide with varying demographies and social mixing patterns.