Pareto rules for malaria super-spreaders and super-spreading

Impact of the intensity of infection in birds on Plasmodium development within Culex pipiens mosquitoes

BACKGROUND

In vector-borne diseases, invertebrate hosts are exposed to highly variable quantities of parasites during their blood meal. This heterogeneity may partly explain the overdispersed distribution of parasites within the vector population and the variability in the extrinsic incubation period (EIP) of the parasite. Indeed, the quantity of parasites ingested is often considered as a good predictor of the quantity of parasites that will develop within the vectors, as well as the speed at which they will develop (i.e. EIP). However, density-dependent processes can influence the relationship between parasite burden in the vertebrate host and in vectors, making this relationship unclear at times.

METHODS

Here, we used an avian malaria system to investigate whether the proportion of red blood cells infected by sexual and/or asexual stages of Plasmodium relictum influences the intensity of infection and the EIP within vectors. For this purpose, we experimentally infected 12 birds in order to generate a range of infection intensity. More than 1000 mosquitoes took a blood meal on these hosts, and the development of Plasmodium within the vectors was followed for more than 20 days.

RESULTS

Our study reveals a negative relationship between the intensity of infection in birds and the time until 10% of mosquitoes become infectious (EIP10). A period of only 4 days was sufficient to detect sporozoites in at least 10% of mosquitoes fed on the most infected hosts. However, the number of sporozoites did not vary significantly according to the vertebrate host intensity of infection, but was positively correlated to the oocyst burden (parasitic stage preceding the sporozoite stage).

CONCLUSIONS

While the quantity of ingested parasites had no impact on oocyst and sporozoite burden in infectious mosquitoes, the EIP10 was affected. Studies have demonstrated that small changes in the EIP can have a significant effect on the number of mosquitoes living long enough to transmit parasites. Here, we observed a difference of 4-6 days in the detection of the first sporozoites, depending on the intensity of infection of the bitten vertebrate host. Considering that a gonotrophic cycle lasts 3-4 days, the shortened EIP may have significant effects on Plasmodium transmission.

Anopheles stephensi larval habitat superproductivity and its relevance for larval source management in Africa

The invasion of Africa by Anopheles stephensi poses a significant threat to malaria elimination. As An. stephensi exploits a wide array of urban artificial larval habitats, it may be less impacted by rainfall variability compared to other native Anopheles species. We empirically investigated this assumption by quantifying the seasonal transition of an established population from eastern Ethiopia between rainy and dry periods. Monthly larval surveys generated evidence of significant heterogeneity between seasons in the type of habitat and their productivity. As the dry season progressed, An. stephensi productivity significantly concentrated in large water reservoirs (for drinking and construction) to a point in which up to 77% of all larvae originated from 23% of the sites. Such superproductive sites were primarily water cisterns used for residential or construction purposes. A two-patch metapopulation model of An. stephensi linked to rainfall data recreated the seasonal larval dynamics observed in the field and predicted that larval control targeted on superproducer water reservoirs, when implemented at coverages higher than 60%, may lead to An. stephensi elimination. Our findings highlight the role of environmental variability in regulating An. stephensi populations and open the window for the deployment of control strategies that exploit major mosquito population bottlenecks.

Disentangling the effects of intermittent faecal shedding and imperfect test sensitivity on the microscopy-based detection of gut parasites in stool samples

BACKGROUND

Gut-parasite transmission often involves faecal shedding, and detecting parasites in stool samples remains the cornerstone of diagnosis. However, not all samples drawn from infected hosts contain parasites (because of intermittent shedding), and no test can detect the target parasites in 100% of parasite-bearing samples (because of imperfect sensitivity). Disentangling the effects of intermittent shedding and imperfect sensitivity on pathogen detection would help us better understand transmission dynamics, disease epidemiology, and diagnostic-test performance. Using paediatric Giardia infections as a case-study, here we illustrate a hierarchical-modelling approach to separately estimating the probabilities of host-level infection ([Formula: see text]); stool-sample-level shedding, given infection ([Formula: see text]); and test-level detection, given infection and shedding ([Formula: see text]).

METHODS/FINDINGS

We collected 1-3 stool samples, in consecutive weeks, from 276 children. Samples (413 overall) were independently examined, via standard sedimentation/optical microscopy, by a senior parasitologist and a junior, trained student (826 tests overall). Using replicate test results and multilevel hierarchical models, we estimated per-sample Giardia shedding probability at [Formula: see text] and observer-specific test sensitivities at [Formula: see text] and [Formula: see text]. Gender-specific infection-frequency estimates were [Formula: see text] and [Formula: see text]. Had we used a (hypothetical) Perfect Test with 100% narrow-sense sensitivity ([Formula: see text]), the average probability of detecting Giardia in a sample drawn from an infected child ([Formula: see text]) would have been [Formula: see text]. Because no test can be >100% sensitive, [Formula: see text] (which measures clinical sensitivity) can only be brought above ~ 0.44 by tinkering with the availability of Giardia in stool samples (i.e., [Formula: see text]); for example, drawing-and-pooling 3 replicate samples would yield [Formula: see text].

CONCLUSIONS

By allowing separate estimation (and modelling) of pathogen-shedding probabilities, the approach we illustrate provides a means to study pathogen transmission cycles and dynamics in unprecedented detail. Separate estimation (and modelling) of true test sensitivity, moreover, may cast new light on the performance of diagnostic tests and procedures, whether novel or routine-practice.

À la carte: how mosquitoes choose their blood meals

Mosquitoes are important vectors for human diseases, transmitting pathogens that cause a range of parasitic and viral infections. Mosquito blood-feeding is heterogeneous, meaning that some human hosts are at higher risk of receiving bites than others, and this heterogeneity is multifactorial. Mosquitoes integrate specific cues to locate their hosts, and mosquito attraction differs considerably between individual human hosts. Heterogeneous mosquito biting results from variations in both host attractiveness and availability and can impact transmission of vector-borne diseases. However, the extent and drivers of this heterogeneity and its importance for pathogen transmission remain incompletely understood. Here, we review methods and recent data describing human characteristics that affect host-seeking behavior and host preferences of mosquito disease vectors, and the implications for vector-borne disease transmission.

Prioritising gully remediation in a Great Barrier Reef catchment: An approach using two independent methods of assessing erosion activity in 22,300 gullies

The strategic reduction and remediation of degraded land is a global environmental priority. This is a particular priority in the Great Barrier Reef catchment area, Australia, where gully erosion a significant contributor to land degradation and water quality deterioration. Urgent action through the prioritisation and remediation of gully erosion sites is imperative to safeguard this UNESCO World Heritage site. In this study, we analyze a comprehensive dataset of 22,311 mapped gullies within a 3480 km2 portion of the lower Burdekin Basin, northeast Australia. Utilizing high-resolution lidar datasets, two independent methods - Minimum Contemporary Estimate (MCE) and Lifetime Average Estimate (LAE) - were developed to derive relative erosion rates. These methods, employing different data processing approaches and addressing different timeframes across the gully lifetime, yield erosion rates varying by up to several orders of magnitude. Despite some expected divergence, both methods exhibit strong, positive correlations with each other and additional validation data. There is a 43% agreement between the methods for the highest yielding 2% of gullies, although 80.5% of high-yielding gullies identified by either method are located within a 1 km proximity of each other. Importantly, distributions from both methods independently reveal that ∼80% of total volume of gully erosion in the study area is produced from only 20% of all gullies. Moreover, the top 2% of gullies generate 30% of the sediment loss and the majority of gullies do not significantly contribute to the overall catchment sediment yield. These results underscore the opportunity to achieve significant environmental outcomes through targeted gully management by prioritising a small cohort of high yielding gullies. Further insights and implications for management frameworks are discussed in the context of the characteristics of this cohort. Overall, this research provides a basis for informed decision-making in addressing gully erosion and advancing environmental conservation efforts.

Arbovirus impact on mosquito behavior: the jury is still out

Parasites can manipulate host behavior to enhance transmission, but our understanding of arbovirus-induced changes in mosquito behavior is limited. Here, we explore current knowledge on such behavioral alterations in mosquito vectors, focusing on host-seeking and blood-feeding behaviors. Reviewing studies on dengue, Zika, La Crosse, Sindbis, and West Nile viruses in Aedes or Culex mosquitoes reveals subtle yet potentially significant effects. However, assay heterogeneity and limited sample sizes challenge definitive conclusions. To enhance robustness, we propose using deep-learning tools for automated behavior quantification and stress the need for standardized assays. Additionally, conducting longitudinal studies across the extrinsic incubation period and integrating diverse traits into modeling frameworks are crucial for understanding the nuanced implications of arbovirus-induced behavioral changes for virus transmission dynamics.

Economic microbiology: exploring microbes as agents in economic systems

Microbial communities exhibit striking parallels with economic markets, resembling intricate ecosystems where microorganisms engage in resource exchange akin to human market transactions. This dynamic network of resource swapping mirrors economic trade in human markets, with microbes specializing in metabolic functions much like businesses specializing in goods and services. Cooperation and competition are central dynamics in microbial communities, with alliances forming for mutual benefit and species vying for dominance, similar to businesses seeking market share. The human microbiome, comprising trillions of microorganisms within and on our bodies, is not only a marker of socioeconomic status but also a critical factor contributing to persistent health inequalities. Social and economic factors shape the composition of the gut microbiota, impacting healthcare access and quality of life. Moreover, these microbes exert indirect influence over human decisions by affecting neurotransmitter production, influencing mood, behavior, and choices related to diet and emotions. Human activities significantly impact microbial communities, from dietary choices and antibiotic use to environmental changes, disrupting these ecosystems. Beyond their natural roles, humans harness microbial communities for various applications, manipulating their interactions and resource exchanges to achieve specific goals in fields like medicine, agriculture, and environmental science. In conclusion, the concept of microbial communities as biological markets offers valuable insights into their intricate functioning and adaptability. It underscores the profound interplay between microbial ecosystems and human health and behavior, with far-reaching implications for multiple disciplines. To paraphrase Alfred Marshall, "the Mecca of the economist lies in economic microbiology."

Susceptible and infectious states for both vector and host in a dynamic pathogen-vector-host system

Deformed wing virus (DWV) is a resurgent insect pathogen of honeybees that is efficiently transmitted by vectors and through host social contact. Continual transmission of DWV between hosts and vectors is required to maintain the pathogen within the population, and this vector-host-pathogen system offers unique disease transmission dynamics for pathogen maintenance between vectors and a social host. In a series of experiments, we measured vector-vector, host-host and host-vector transmission routes and show how these maintain DWV in honeybee populations. We found co-infestations on shared hosts allowed for movement of DWV from mite to mite. Additionally, two social behaviours of the honeybee, trophallaxis and cannibalization of pupae, provide routes for horizontal transmission from bee to bee. Circulation of the virus solely among hosts through communicable modes provides a reservoir of DWV for naïve Varroa to acquire and subsequently vector the pathogen. Our findings illustrate the importance of community transmission between hosts and vector transmission. We use these results to highlight the key avenues used by DWV during maintenance and infection and point to similarities with a handful of other infectious diseases of zoonotic and medical importance.

Real-time PCR detection of mixed Plasmodium ovale curtisi and wallikeri species infections in human and mosquito hosts

Plasmodium ovale curtisi (Poc) and Plasmodium ovale wallikeri (Pow) represent distinct non-recombining malaria species that are increasing in prevalence in sub-Saharan Africa. Though they circulate sympatrically, co-infection within human and mosquito hosts has rarely been described. Separate 18S rRNA real-time PCR assays that detect Poc and Pow were modified to allow species determination in parallel under identical cycling conditions. The lower limit of detection was 0.6 plasmid copies/μL (95% CI 0.4-1.6) for Poc and 4.5 plasmid copies/μL (95% CI( 2.7- 18) for Pow, or 0.1 and 0.8 parasites/μL, respectively, assuming 6 copies of 18s rRNA per genome. However, the assays showed cross-reactivity at concentrations greater than 103 plasmid copies/μL (roughly 200 parasites/μL). Mock mixtures were used to establish criteria for classifying mixed Poc/Pow infections that prevented false-positive detection while maintaining sensitive detection of the minority ovale species down to 10° copies/μL (<1 parasite/μL). When the modified real-time PCR assays were applied to field-collected blood samples from Tanzania and Cameroon, species identification by real-time PCR was concordant with nested PCR, but additionally detected two mixed Poc/Pow infections where nested PCR detected a single Po species. When real-time PCR was applied to 14 oocyst-positive Anopheles midguts saved from mosquitoes fed on P. ovate-infected persons, mixed Poc/Pow infections were detected in 11 (79%). Based on these results, 8/9 P. ovate carriers transmitted both P. ovate species to mosquitoes, though both Po species could only be detected in the blood of two carriers. The described real-time PCR approach can be used to identify the natural occurrence of mixed Poc/Pow infections in human and mosquito hosts and reveals that such co-infections and co-transmission are likely more common than appreciated.

Inapparent infections shape the transmission heterogeneity of dengue

Transmission heterogeneity, whereby a disproportionate fraction of pathogen transmission events result from a small number of individuals or geographic locations, is an inherent property of many, if not most, infectious disease systems. For vector-borne diseases, transmission heterogeneity is inferred from the distribution of the number of vectors per host, which could lead to significant bias in situations where vector abundance and transmission risk at the household do not correlate, as is the case with dengue virus (DENV). We used data from a contact tracing study to quantify the distribution of DENV acute infections within human activity spaces (AS), the collection of residential locations an individual routinely visits, and quantified measures of virus transmission heterogeneity from two consecutive dengue outbreaks (DENV-4 and DENV-2) that occurred in the city of Iquitos, Peru. Negative-binomial distributions and Pareto fractions showed evidence of strong overdispersion in the number of DENV infections by AS and identified super-spreading units (SSUs): i.e. AS where most infections occurred. Approximately 8% of AS were identified as SSUs, contributing to more than 50% of DENV infections. SSU occurrence was associated more with DENV-2 infection than with DENV-4, a predominance of inapparent infections (74% of all infections), households with high Aedes aegypti mosquito abundance, and high host susceptibility to the circulating DENV serotype. Marked heterogeneity in dengue case distribution, and the role of inapparent infections in defining it, highlight major challenges faced by reactive interventions if those transmission units contributing the most to transmission are not identified, prioritized, and effectively treated.

Evidence for exposure dependent carriage of malaria parasites across the dry season: modelling analysis of longitudinal data

BACKGROUND

In malaria endemic regions, transmission of Plasmodium falciparum parasites is often seasonal with very low transmission during the dry season and high transmission in the wet season. Parasites survive the dry season within some individuals who experience prolonged carriage of parasites and are thought to 'seed' infection in the next transmission season.

METHODS

Dry season carriers and their role in the subsequent transmission season are characterized using a combination of mathematical simulations and data analysis of previously described data from a longitudinal study in Mali of individuals aged 3 months-12 years (n = 579).

RESULTS

Simulating the life-history of individuals experiencing repeated exposure to infection predicts that dry season carriage is more likely in the oldest, most exposed and most immune individuals. This hypothesis is supported by the data from Mali, which shows that carriers are significantly older, experience a higher biting rate at the beginning of the transmission season and develop clinical malaria later than non-carriers. Further, since the most exposed individuals in a community are most likely to be dry season carriers, this is predicted to enable a more than twofold faster spread of parasites into the mosquito population at the start of the subsequent wet season.

CONCLUSIONS

Carriage of malaria parasites over the months-long dry season in Mali is most likely in the older, more exposed and more immune children. These children may act as super-spreaders facilitating the fast spread of parasites at the beginning of the next transmission season.

Promiscuous feeding on multiple adult honey bee hosts amplifies the vectorial capacity of Varroa destructor

Varroa destructor is a cosmopolitan pest and leading cause of colony loss of the European honey bee. Historically described as a competent vector of honey bee viruses, this arthropod vector is the cause of a global pandemic of Deformed wing virus, now endemic in honeybee populations in all Varroa-infested regions. Our work shows that viral spread is driven by Varroa actively switching from one adult bee to another as they feed. Assays using fluorescent microspheres were used to indicate the movement of fluids in both directions between host and vector when Varroa feed. Therefore, Varroa could be in either an infectious or naïve state dependent upon the disease status of their host. We tested this and confirmed that the relative risk of a Varroa feeding depended on their previous host's infectiousness. Varroa exhibit remarkable heterogeneity in their host-switching behavior, with some Varroa infrequently switching while others switch at least daily. As a result, relatively few of the most active Varroa parasitize the majority of bees. This multiple-feeding behavior has analogs in vectorial capacity models of other systems, where promiscuous feeding by individual vectors is a leading driver of vectorial capacity. We propose that the honeybee-Varroa relationship offers a unique opportunity to apply principles of vectorial capacity to a social organism, as virus transmission is both vectored and occurs through multiple host-to-host routes common to a crowded society.

Individual variation in Plasmodium vivax malaria risk: Are repeatedly infected people just unlucky?

Extensive research has examined why some people have frequent Plasmodium falciparum malaria episodes in sub-Saharan Africa while others remain free of disease most of the time. In contrast, malaria risk heterogeneity remains little studied in regions where P. vivax is the dominant species. Are repeatedly infected people in vivax malaria settings such as the Amazon just unlucky? Here, we briefly review evidence that human genetic polymorphism and acquired immunity after repeated exposure to parasites can modulate the risk of P. vivax infection and disease in predictable ways. One-fifth of the hosts account for 80% or more of the community-wide vivax malaria burden and contribute disproportionally to onward transmission, representing a priority target of more intensive interventions to achieve malaria elimination. Importantly, high-risk individuals eventually develop clinical immunity, even in areas with very low or residual malaria transmission, and may constitute a large but silent parasite reservoir.

Population heterogeneity in Plasmodium vivax relapse risk

A key characteristic of Plasmodium vivax parasites is their ability to adopt a latent liver-stage form called hypnozoites, able to cause relapse of infection months or years after a primary infection. Relapses of infection through hypnozoite activation are a major contributor to blood-stage infections in P vivax endemic regions and are thought to be influenced by factors such as febrile infections which may cause temporary changes in hypnozoite activation leading to 'temporal heterogeneity' in reactivation risk. In addition, immunity and variation in exposure to infection may be longer-term characteristics of individuals that lead to 'population heterogeneity' in hypnozoite activation. We analyze data on risk of P vivax in two previously published data sets from Papua New Guinea and the Thailand-Myanmar border region. Modeling different mechanisms of reactivation risk, we find strong evidence for population heterogeneity, with 30% of patients having almost 70% of all P vivax infections. Model fitting and data analysis indicates that individual variation in relapse risk is a primary source of heterogeneity of P vivax risk of recurrences. Trial Registration: ClinicalTrials.gov NCT01640574, NCT01074905, NCT02143934.

Different forms of superspreading lead to different outcomes: Heterogeneity in infectiousness and contact behavior relevant for the case of SARS-CoV-2

Superspreading events play an important role in the spread of several pathogens, such as SARS-CoV-2. While the basic reproduction number of the original Wuhan SARS-CoV-2 is estimated to be about 3 for Belgium, there is substantial inter-individual variation in the number of secondary cases each infected individual causes-with most infectious individuals generating no or only a few secondary cases, while about 20% of infectious individuals is responsible for 80% of new infections. Multiple factors contribute to the occurrence of superspreading events: heterogeneity in infectiousness, individual variations in susceptibility, differences in contact behavior, and the environment in which transmission takes place. While superspreading has been included in several infectious disease transmission models, research into the effects of different forms of superspreading on the spread of pathogens remains limited. To disentangle the effects of infectiousness-related heterogeneity on the one hand and contact-related heterogeneity on the other, we implemented both forms of superspreading in an individual-based model describing the transmission and spread of SARS-CoV-2 in a synthetic Belgian population. We considered its impact on viral spread as well as on epidemic resurgence after a period of social distancing. We found that the effects of superspreading driven by heterogeneity in infectiousness are different from the effects of superspreading driven by heterogeneity in contact behavior. On the one hand, a higher level of infectiousness-related heterogeneity results in a lower risk of an outbreak persisting following the introduction of one infected individual into the population. Outbreaks that did persist led to fewer total cases and were slower, with a lower peak which occurred at a later point in time, and a lower herd immunity threshold. Finally, the risk of resurgence of an outbreak following a period of lockdown decreased. On the other hand, when contact-related heterogeneity was high, this also led to fewer cases in total during persistent outbreaks, but caused outbreaks to be more explosive in regard to other aspects (such as higher peaks which occurred earlier, and a higher herd immunity threshold). Finally, the risk of resurgence of an outbreak following a period of lockdown increased. We found that these effects were conserved when testing combinations of infectiousness-related and contact-related heterogeneity.

Hotspots and super-spreaders: Modelling fine-scale malaria parasite transmission using mosquito flight behaviour

Malaria hotspots have been the focus of public health managers for several years due to the potential elimination gains that can be obtained from targeting them. The identification of hotspots must be accompanied by the description of the overall network of stable and unstable hotspots of malaria, especially in medium and low transmission settings where malaria elimination is targeted. Targeting hotspots with malaria control interventions has, so far, not produced expected benefits. In this work we have employed a mechanistic-stochastic algorithm to identify clusters of super-spreader houses and their related stable hotspots by accounting for mosquito flight capabilities and the spatial configuration of malaria infections at the house level. Our results show that the number of super-spreading houses and hotspots is dependent on the spatial configuration of the villages. In addition, super-spreaders are also associated to house characteristics such as livestock and family composition. We found that most of the transmission is associated with winds between 6pm and 10pm although later hours are also important. Mixed mosquito flight (downwind and upwind both with random components) were the most likely movements causing the spread of malaria in two out of the three study areas. Finally, our algorithm (named MALSWOTS) provided an estimate of the speed of malaria infection progression from house to house which was around 200-400 meters per day, a figure coherent with mark-release-recapture studies of Anopheles dispersion. Cross validation using an out-of-sample procedure showed accurate identification of hotspots. Our findings provide a significant contribution towards the identification and development of optimal tools for efficient and effective spatio-temporal targeted malaria interventions over potential hotspot areas.

Over-dispersed Trypanosoma cruzi parasite load in sylvatic and domestic mammals and humans from northeastern Argentina

BACKGROUND

The distribution of parasite load across hosts may modify the transmission dynamics of infectious diseases. Chagas disease is caused by a multi-host protozoan, Trypanosoma cruzi, but the association between host parasitemia and infectiousness to the vector has not been studied in sylvatic mammalian hosts. We quantified T. cruzi parasite load in sylvatic mammals, modeled the association of the parasite load with infectiousness to the vector and compared these results with previous ones for local domestic hosts.

METHODS

The bloodstream parasite load in each of 28 naturally infected sylvatic mammals from six species captured in northern Argentina was assessed by quantitative PCR, and its association with infectiousness to the triatomine Triatoma infestans was evaluated, as determined by natural or artificial xenodiagnosis. These results were compared with our previous results for 88 humans, 70 dogs and 13 cats, and the degree of parasite over-dispersion was quantified and non-linear models fitted to data on host infectiousness and bloodstream parasite load.

RESULTS

The parasite loads of Didelphis albiventris (white-eared opossum) and Dasypus novemcinctus (nine-banded armadillo) were directly and significantly associated with infectiousness of the host and were up to 190-fold higher than those in domestic hosts. Parasite load was aggregated across host species, as measured by the negative binomial parameter, k, and found to be substantially higher in white-eared opossums, cats, dogs and nine-banded armadillos (range: k = 0.3-0.5) than in humans (k = 5.1). The distribution of bloodstream parasite load closely followed the "80-20 rule" in every host species examined. However, the 20% of human hosts, domestic mammals or sylvatic mammals exhibiting the highest parasite load accounted for 49, 25 and 33% of the infected triatomines, respectively.

CONCLUSIONS

Our results support the use of bloodstream parasite load as a proxy of reservoir host competence and individual transmissibility. The over-dispersed distribution of T. cruzi bloodstream load implies the existence of a fraction of highly infectious hosts that could be targeted to improve vector-borne transmission control efforts toward interruption transmission. Combined strategies that decrease the parasitemia and/or host-vector contact with these hosts would disproportionally contribute to T. cruzi transmission control.

How radical is radical cure? Site-specific biases in clinical trials underestimate the effect of radical cure on Plasmodium vivax hypnozoites

BACKGROUND

Plasmodium vivax blood-stage relapses originating from re-activating hypnozoites are a major barrier for control and elimination of this disease. Radical cure is a form of therapy capable of addressing this problem. Recent clinical trials of radical cure have yielded efficacy estimates ranging from 65 to 94%, with substantial variation across trial sites.

METHODS

An analysis of simulated trial data using a transmission model was performed to demonstrate that variation in efficacy estimates across trial sites can arise from differences in the conditions under which trials are conducted.

RESULTS

The analysis revealed that differences in transmission intensity, heterogeneous exposure and relapse rate can yield efficacy estimates ranging as widely as 12-78%, despite simulating trial data under the uniform assumption that treatment had a 75% chance of clearing hypnozoites. A longer duration of prophylaxis leads to a greater measured efficacy, particularly at higher transmission intensities, making the comparison between the protection of different radical cure treatment regimens against relapse more challenging. Simulations show that vector control and parasite genotyping offer two potential means to yield more standardized efficacy estimates that better reflect prevention of relapse.

CONCLUSIONS

Site-specific biases are likely to contribute to variation in efficacy estimates both within and across clinical trials. Future clinical trials can reduce site-specific biases by conducting trials in low-transmission settings where re-infections from mosquito bite are less common, by preventing re-infections using vector control measures, or by identifying and excluding likely re-infections that occur during follow-up, by using parasite genotyping methods.

Household and individual level risk factors associated with declining malaria incidence in Meghalaya, India: implications for malaria elimination in low-endemic settings

Background

A detailed analysis of household and individual level Plasmodium infection patterns in two low-endemic districts of Meghalaya was undertaken to better understand the epidemiology of malaria in northeast India.

Methods

Socio-demographic and behavioural information from residents (aged 1–69 years) of households were collected through pre-tested, questionnaire conducted in 2018 and 2019. Blood samples collected from participants were tested for Plasmodium falciparum and/or Plasmodium vivax infection using rapid diagnostic test, microscopy and PCR. Plasma samples from a subset of participants were analysed for antibodies against thirteen P. falciparum and four P. vivax antigens. Associations between household and individual level risk factors, and Plasmodium infections were evaluated using multilevel logistic regression models.

Results

A total of 2753 individuals from 827 households were enrolled in 2018, and 834 individuals from 222 households were enrolled in 2019. Of them, 33 (1.2%) were positive by PCR for P. falciparum in 2018 and none were positive for P. vivax. In 2019, no PCR-positive individuals were detected. All, but one, infections were asymptomatic; all 33 infections were sub-microscopic. Reported history of malaria in the past 12 months (OR = 8.84) and history of travel in the past 14 days (OR = 10.06) were significantly associated with Plasmodium infection. A significant trend of increased seropositivity with age was noted for all 17 antigens. Although adults (≥ 18 years) consistently had the highest seropositivity rates, a sizeable proportion of under-five children were also found to be seropositive. Almost all individuals (99.4%) reported sleeping under an insecticide-treated bed-net, and household indoor residual spray coverage in the 12 months preceding the survey was low (23%). Most participants correctly identified common signs and symptoms of malaria, i.e., fever (96.4%), headache (71.2%), chills (83.2%) and body-ache (61.8%). Almost all participants (94.3%) used government-provided services for treatment of malaria.

Conclusion

This study explored the epidemiology of malaria in two communities in Meghalaya, India, in the context of declining transmission. The presence of widespread asymptomatic infections and seropositivity among under-five children suggest that low-level Plasmodium transmission persists in this region. Implications of the study findings for malaria elimination efforts in low-transmission settings are discussed.

Persistent Plasmodium falciparum infections enhance transmission-reducing immunity development

Subclinical infections that serve as reservoir populations to drive transmission remain a hurdle to malaria control. Data on infection dynamics in a geographical area is required to strategically design and implement malaria interventions. In a longitudinal cohort, we monitored Plasmodium falciparum infection prevalence and persistence, and anti-parasite immunity to gametocyte and asexual antigens for 10 weeks. Of the 100 participants, only 11 were never infected, whilst 16 had persistent infections detected by reverse transcriptase-quantitative polymerase chain reaction (RT-qPCR), and one participant had microscopic parasites at all visits. Over 70% of the participants were infected three or more times, and submicroscopic gametocyte prevalence was high, ≥ 48% of the parasite carriers. Naturally induced responses against recombinant Pfs48/45.6C, Pfs230proC, and EBA175RIII-V antigens were not associated with either infection status or gametocyte carriage, but the antigen-specific IgG titers inversely correlated with parasite and gametocyte densities consistent with partial immunity. Longitudinal analysis of gametocyte diversity indicated at least four distinct clones circulated throughout the study period. The high prevalence of children infected with distinct gametocyte clones coupled with marked variation in infection status at the individual level suggests ongoing transmission and should be targeted in malaria control programs.

Isolation, Identification, and Selection of Bacteria With Proof-of-Concept for Bioaugmentation of Whitewater From Wood-Free Paper Mills

In the wood-free paper industry, whitewater is usually a mixture of additives for paper production. We are currently lacking an efficient, cost-effective purification technology for their removal. In closed whitewater cycles the additives accumulate, causing adverse production problems, such as the formation of slime and pitch. The aim of our study was to find an effective bio-based strategy for whitewater treatment using a selection of indigenous bacterial isolates. We first obtained a large collection of bacterial isolates and then tested them individually by simple plate and spectrophotometric methods for their ability to degrade the papermaking additives, i.e., carbohydrates, resin acids, alkyl ketene dimers, polyvinyl alcohol, latex, and azo and fluorescent dyes. We examined correlation between carbon source use, genera, and inoculum source of isolates using two multivariate methods: principal component analysis and FreeViz projection. Of the 318 bacterial isolates, we selected a consortium of four strains (Xanthomonadales bacterium sp. CST37-CF, Sphingomonas sp. BLA14-CF, Cellulosimicrobium sp. AKD4-BF and Aeromonas sp. RES19-BTP) that degrade the entire spectrum of tested additives by means of dissolved organic carbon measurements. A proof-of-concept study on a pilot scale was then performed by immobilizing the artificial consortium of the four strains and inserting them into a 33-liter, tubular flow-through reactor with a retention time of < 15 h. The consortium caused an 88% reduction in the COD of the whitewater, even after 21 days.

Nonrandom Selection and Multiple Blood Feeding of Human Hosts by Anopheles Vectors: Implications for Malaria Transmission in Papua New Guinea

Nonrandom selection and multiple blood feeding of human hosts by Anopheles mosquitoes may exacerbate malaria transmission. Both patterns of blood feeding and their relationship to malaria epidemiology were investigated in Anopheles vectors in Papua New Guinea (PNG). Blood samples from humans and mosquito blood meals were collected in villages and human genetic profiles ("fingerprints") were analyzed by genotyping 23 microsatellites and a sex-specific marker. Frequency of blood meals acquired from different humans, identified by unique genetic profiles, was fitted to Poisson and negative binomial distributions to test for nonrandom patterns of host selection. Blood meals with more than one genetic profiles were classified as mosquitoes that fed on multiple humans. The age of a person bitten by a mosquito was determined by matching the blood-meal genetic profile to the villagers' genetic profiles. Malaria infection in humans was determined by PCR test of blood samples. The results show nonrandom distribution of blood feeding among humans, with biased selection toward males and individuals aged 15-30 years. Prevalence of Plasmodium falciparum infection was higher in this age group, suggesting males in this age range could be super-spreaders of malaria parasites. The proportion of mosquitoes that fed on multiple humans ranged from 6% to 13% among villages. The patterns of host utilization observed here can amplify transmission and contribute to the persistence of malaria in PNG despite efforts to suppress it with insecticidal bed nets. Excessive feeding on males aged 15-30 years underscores the importance of targeted interventions focusing on this demographic group.

Measuring the accuracy of gridded human population density surfaces: A case study in Bioko Island, Equatorial Guinea

Background

Geospatial datasets of population are becoming more common in models used for health policy. Publicly-available maps of human population make a consistent picture from inconsistent census data, and the techniques they use to impute data makes each population map unique. Each mapping model explains its methods, but it can be difficult to know which map is appropriate for which policy work. High quality census datasets, where available, are a unique opportunity to characterize maps by comparing them with truth.

Methods

We use census data from a bed-net mass-distribution campaign on Bioko Island, Equatorial Guinea, conducted by the Bioko Island Malaria Elimination Program as a gold standard to evaluate LandScan (LS), WorldPop Constrained (WP-C) and WorldPop Unconstrained (WP-U), Gridded Population of the World (GPW), and the High-Resolution Settlement Layer (HRSL). Each layer is compared to the gold-standard using statistical measures to evaluate distribution, error, and bias. We investigated how map choice affects burden estimates from a malaria prevalence model.

Results

Specific population layers were able to match the gold-standard distribution at different population densities. LandScan was able to most accurately capture highly urban distribution, HRSL and WP-C matched best at all other lower population densities. GPW and WP-U performed poorly everywhere. Correctly capturing empty pixels is key, and smaller pixel sizes (100 m vs 1 km) improve this. Normalizing areas based on known district populations increased performance. The use of differing population layers in a malaria model showed a disparity in results around transition points between endemicity levels.

Discussion

The metrics in this paper, some of them novel in this context, characterize how these population maps differ from the gold standard census and from each other. We show that the metrics help understand the performance of a population map within a malaria model. The closest match to the census data would combine LandScan within urban areas and the HRSL for rural areas. Researchers should prefer particular maps if health calculations have a strong dependency on knowing where people are not, or if it is important to categorize variation in density within a city.

Early prognosis of respiratory virus shedding in humans

This paper addresses the development of predictive models for distinguishing pre-symptomatic infections from uninfected individuals. Our machine learning experiments are conducted on publicly available challenge studies that collected whole-blood transcriptomics data from individuals infected with HRV, RSV, H1N1, and H3N2. We address the problem of identifying discriminatory biomarkers between controls and eventual shedders in the first 32 h post-infection. Our exploratory analysis shows that the most discriminatory biomarkers exhibit a strong dependence on time over the course of the human response to infection. We visualize the feature sets to provide evidence of the rapid evolution of the gene expression profiles. To quantify this observation, we partition the data in the first 32 h into four equal time windows of 8 h each and identify all discriminatory biomarkers using sparsity-promoting classifiers and Iterated Feature Removal. We then perform a comparative machine learning classification analysis using linear support vector machines, artificial neural networks and Centroid-Encoder. We present a range of experiments on different groupings of the diseases to demonstrate the robustness of the resulting models.

Human-Mosquito Contact: A Missing Link in Our Understanding of Mosquito-Borne Disease Transmission Dynamics

Despite the critical role that contact between hosts and vectors, through vector bites, plays in driving vector-borne disease (VBD) transmission, transmission risk is primarily studied through the lens of vector density and overlooks host-vector contact dynamics. This review article synthesizes current knowledge of host-vector contact with an emphasis on mosquito bites. It provides a framework including biological and mathematical definitions of host-mosquito contact rate, blood-feeding rate, and per capita biting rates. We describe how contact rates vary and how this variation is influenced by mosquito and vertebrate factors. Our framework challenges a classic assumption that mosquitoes bite at a fixed rate determined by the duration of their gonotrophic cycle. We explore alternative ecological assumptions based on the functional response, blood index, forage ratio, and ideal free distribution within a mechanistic host-vector contact model. We highlight that host-vector contact is a critical parameter that integrates many factors driving disease transmission. A renewed focus on contact dynamics between hosts and vectors will contribute new insights into the mechanisms behind VBD spread and emergence that are sorely lacking. Given the framework for including contact rates as an explicit component of mathematical models of VBD, as well as different methods to study contact rates empirically to move the field forward, researchers should explicitly test contact rate models with empirical studies. Such integrative studies promise to enhance understanding of extrinsic and intrinsic factors affecting host-vector contact rates and thus are critical to understand both the mechanisms driving VBD emergence and guiding their prevention and control.

Non-immune Traits Triggered by Blood Intake Impact Vectorial Competence

Blood-feeding arthropods are considered an enormous public health threat. They are vectors of a plethora of infectious agents that cause potentially fatal diseases like Malaria, Dengue fever, Leishmaniasis, and Lyme disease. These vectors shine due to their own physiological idiosyncrasies, but one biological aspect brings them all together: the requirement of blood intake for development and reproduction. It is through blood-feeding that they acquire pathogens and during blood digestion that they summon a collection of multisystemic events critical for vector competence. The literature is focused on how classical immune pathways (Toll, IMD, and JAK/Stat) are elicited throughout the course of vector infection. Still, they are not the sole determinants of host permissiveness. The dramatic changes that are the hallmark of the insect physiology after a blood meal intake are the landscape where a successful infection takes place. Dominant processes that occur in response to a blood meal are not canonical immunological traits yet are critical in establishing vector competence. These include hormonal circuitries and reproductive physiology, midgut permeability barriers, midgut homeostasis, energy metabolism, and proteolytic activity. On the other hand, the parasites themselves have a role in the outcome of these blood triggered physiological events, consistently using them in their favor. Here, to enlighten the knowledge on vector-pathogen interaction beyond the immune pathways, we will explore different aspects of the vector physiology, discussing how they give support to these long-dated host-parasite relationships.

The top 1%: quantifying the unequal distribution of malaria in Brazil

Background

As malaria endemic countries strive towards elimination, intensified spatial heterogeneities of local transmission could undermine the effectiveness of traditional intervention policy.

Methods

The dynamic nature of large-scale and long-term malaria heterogeneity across Brazilian Amazon basin were explored by (1) exploratory analysis of Brazil’s rich clinical malaria reporting database from 2004 to 2018, and (2) adapting Gini coefficient to study the distribution of malaria cases in the region.

Results

As transmission declined, heterogeneity increased with cases clustering into smaller subpopulations across the territory. In 2004, the 1% of health units with the greatest number of cases accounted for 46% of all reported Plasmodium vivax cases, whereas in 2018 52% of P. vivax cases occurred in the top 1% of health units. Plasmodium falciparum had lower levels of transmission than P. vivax, and also had greater levels of heterogeneity with 75% of cases occurring in the top 1% of health units. Age and gender stratification of cases revealed peri-domestic and occupational exposure settings that remained relatively stable.

Conclusion

The pathway to decreasing incidence is characterized by higher proportions of cases in males, in adults, due to importation, and caused by P. vivax. Characterization of spatio-temporal heterogeneity and risk groups can aid stratification for improved malaria control towards elimination with increased heterogeneity potentially allowing for more efficient and cost-effective targeting. Although distinct epidemiological phenomena were clearly observed as malaria transmission declines, the authors argue that there is no canonical path to malaria elimination and a more targeted and dynamic surveillance will be needed if Brazil decides to adopt the elimination target.

Superspreaders: A Lurking Danger in the Community

A "superspreader" refers to an unusually contagious organism infected with a disease. With respect to a human borne illnesses, a superspreader is someone who is more likely to infect other humans when compared to a typically infected person. The existence of human superspreaders is deeply entrenched in history; the most famous case being that of Typhoid Mary. Through contact tracing, epidemiologists have identified human superspreaders in measles, tuberculosis, rubella, monkeypox, smallpox, Ebola hemorrhagic fever, and SARS. The recent outbreak of Coronavirus disease (COVID-19) has shifted the focus back on the superspreaders. We herein present a case report of a COVID-19 superspreader with a hitherto unusually high number of infected contacts. The index case was a 33 year old male who resided in a low income settlement comprising of rehabilitated slum dwellers and worked as a healthcare worker (HCW) in a tertiary care hospital and had tested positive for COVID-19.On contact tracing, he had a total of 125 contacts, of which 49 COVID-19 infections had direct or indirect contact with the index case, qualifying him as a "superspreader." This propagated infection led to an outbreak in the community. Contact tracing, testing and isolation of such superspreaders from the other members of the community is essential to stop the spread of this disease and contain the COVID-19 pandemic.

Characterizing superspreading of SARS-CoV-2 : from mechanism to measurement

Superspreading is a ubiquitous feature of SARS-CoV-2 transmission dynamics, with a few primary infectors leading to a large proportion of secondary infections. Despite the superspreading events observed in previous coronavirus outbreaks, the mechanisms behind the phenomenon are still poorly understood. Here, we show that superspreading is largely driven by heterogeneity in contact behavior rather than heterogeneity in susceptibility or infectivity caused by biological factors. We find that highly heterogeneous contact behavior is required to produce the extreme superspreading estimated from recent COVID-19 outbreaks. However, we show that superspreading estimates are noisy and subject to biases in data collection and public health capacity, potentially leading to an overestimation of superspreading. These results suggest that superspreading for COVID-19 is substantial, but less than previously estimated. Our findings highlight the complexity inherent to quantitative measurement of epidemic dynamics and the necessity of robust theory to guide public health intervention.

A Model for Assessing the Quantitative Effects of Heterogeneous Affinity in Malaria Transmission along with Ivermectin Mass Administration

Using an agent-based model of malaria, we present numerical evidence that in communities of individuals having an affinity varying within a broad range of values, disease transmission may increase up to 300%. Moreover, our findings provide new insight into how to combine different strategies for the prevention of malaria transmission. In particular, we uncover a relationship between the level of heterogeneity and the level of conventional and unconventional anti-malarial drug administration (ivermectin and gametocidal agents), which, when taken together, will define a control parameter, tuning between disease persistence and elimination. Finally, we also provide evidence that the entomological inoculation rate, as well as the product between parasite and sporozoite rates are both good indicators of malaria incidence in the presence of heterogeneity in disease transmission and may configure a possible improvement in that setting, upon classical standard measures such as the basic reproductive number.

Risk assessment of postoperative pneumonia among children undergoing otolaryngologic surgery: Derivation and validation of a preoperative risk profiling

BACKGROUND

Postoperative pneumonia is a serious complication because it may be associated with morbidity, mortality and substantially increased cost of surgical care. Risk of postoperative pneumonia varies across surgical specialties, although its incidence and risk factors in pediatric otolaryngology have not been comprehensively elucidated.

OBJECTIVE

To identify factors associated with postoperative pneumonia and determine whether a subset of children with a disproportionate risk of pneumonia can be identified.

METHODS

Using the National Surgical Quality Improvement- Pediatric (NSQIP-P) database, we first selected children (N = 17,776; age under 18 years) who underwent inpatient pediatric otolaryngology procedures between 2012 and 2017. Using a random subset of 80% of the study population (derivation cohort), we next developed a multivariable logistic regression model to identify independent risk factors for postoperative pneumonia. We then divided children into risk groups and evaluated whether the Pareto principle applied to distribution of postoperative pneumonia across the risk groups.

RESULTS

Among the 12,443 children in the derivation cohort, 177 (1.4%) developed postoperative pneumonia. A multivariable risk model identified patients who developed postoperative pneumonia with good accuracy in both the derivation and validation cohorts. Stratification of patients into five mutually exclusive risk groups showed that 71% of postoperative pneumonia occurred in the highest risk group representing 20% the study cohort. Children who developed postoperative pneumonia were 18 times more likely to require an extended hospital length of stay (OR: 18.6; 95%CI: 12.3-28.2), and 7 times more likely to die compared to children without pneumonia (OR: 7.40, 95%CI: 3.53-15.48).

CONCLUSIONS

We identified key preoperative risk factors for postoperative pneumonia in children undergoing otolaryngology surgery. A small proportion (20%) of high-risk patients accounted for a large proportion (71%) of postoperative pneumonia indicating an underlying Pareto distribution and underscoring the need for targeted interventions for this "vital few". Postoperative pneumonia in pediatric otolaryngology surgical inpatients was associated with longer hospital stay and a higher risk of mortality.

CLINICAL TRIAL NUMBER AND REGISTRY

Not applicable.

A New Test of a Theory about Old Mosquitoes

In vector control, it is widely accepted that killing adult mosquitoes would sharply reduce the proportion of old mosquitoes and cause the greatest changes to malaria transmission. The principle is based on a mathematical model of the sporozoite rate (the proportion of infective mosquitoes) that emphasized changes in mosquito age. Killing adult mosquitoes also reduces mosquito population densities, which are directly proportional to human biting rates (the number of bites, per person, per day). Eect sizes of vector control can be compared using sporozoite rates and human biting rates, which are commonly measured. We argue that human biting rates convey more use- ful information for planning, monitoring and evaluating vector control, and operational research should focus on understanding mosquito ecology.

Last-come, best served? Mosquito biting order and Plasmodium transmission

A pervasive characteristic of parasite infections is their tendency to be overdispersed. Understanding the mechanisms underlying this overdispersed distribution is of key importance as it may impact the transmission dynamics of the pathogen. Although multiple factors ranging from environmental stochasticity to inter-individual heterogeneity may explain parasite overdispersion, parasite infection is also overdispersed in an inbred host population maintained under laboratory conditions, suggesting that other mechanisms are at play. Here, we show that the aggregated distribution of malaria parasites within mosquito vectors is partially explained by a temporal heterogeneity in parasite infectivity triggered by the bites of mosquitoes. Parasite transmission tripled between the mosquito's first and last blood feed in a period of only 3 h. Surprisingly, the increase in transmission is not associated with an increase in parasite investment in production of the transmissible stage. Overall, we highlight that Plasmodium is capable of responding to the bites of mosquitoes to increase its own transmission at a much faster pace than initially thought and that this is partly responsible for overdispersed distribution of infection. We discuss the underlying mechanisms as well as the broader implications of this plastic response for the epidemiology of malaria.

Fast Response to Superspreading: Uncertainty and Complexity in the Context of COVID-19

Although the first coronavirus disease 2019 (COVID-19) wave has peaked with the second wave underway, the world is still struggling to manage potential systemic risks and unpredictability of the pandemic. A particular challenge is the "superspreading" of the virus, which starts abruptly, is difficult to predict, and can quickly escalate into medical and socio-economic emergencies that contribute to long-lasting crises challenging our current ways of life. In these uncertain times, organizations and societies worldwide are faced with the need to develop appropriate strategies and intervention portfolios that require fast understanding of the complex interdependencies in our world and rapid, flexible action to contain the spread of the virus as quickly as possible, thus preventing further disastrous consequences of the pandemic. We integrate perspectives from systems sciences, epidemiology, biology, social networks, and organizational research in the context of the superspreading phenomenon to understand the complex system of COVID-19 pandemic and develop suggestions for interventions aimed at rapid responses.

Community-level impacts of spatial repellents for control of diseases vectored by Aedes aegypti mosquitoes

Spatial repellents (SRs) reduce human-mosquito contact by preventing mosquito entrance into human-occupied spaces and interfering with host-seeking and blood-feeding. A new model to synthesize experimental data on the effects of transfluthrin on Aedes aegypti explores how SR effects interact to impact the epidemiology of diseases vectored by these mosquitoes. Our results indicate that the greatest impact on force of infection is expected to derive from the chemical's lethal effect but delayed biting and the negative effect this may have on the mosquito population could elicit substantial impact in the absence of lethality. The relative contributions of these effects depend on coverage, chemical dose, and housing density. We also demonstrate that, through an increase in the number of potentially infectious mosquito bites, increased partial blood-feeding and reduced exiting may elicit adverse impacts, which could offset gains achieved by other effects. Our analysis demonstrates how small-scale experimental data can be leveraged to derive expectations of epidemiological impact of SRs deployed at larger scales.

Vector bionomics and vectorial capacity as emergent properties of mosquito behaviors and ecology

Mosquitoes are important vectors for pathogens that infect humans and other vertebrate animals. Some aspects of adult mosquito behavior and mosquito ecology play an important role in determining the capacity of vector populations to transmit pathogens. Here, we re-examine factors affecting the transmission of pathogens by mosquitoes using a new approach. Unlike most previous models, this framework considers the behavioral states and state transitions of adult mosquitoes through a sequence of activity bouts. We developed a new framework for individual-based simulation models called MBITES (Mosquito Bout-based and Individual-based Transmission Ecology Simulator). In MBITES, it is possible to build models that simulate the behavior and ecology of adult mosquitoes in exquisite detail on complex resource landscapes generated by spatial point processes. We also developed an ordinary differential equation model which is the Kolmogorov forward equations for models developed in MBITES under a specific set of simplifying assumptions. While mosquito infection and pathogen development are one possible part of a mosquito's state, that is not our main focus. Using extensive simulation using some models developed in MBITES, we show that vectorial capacity can be understood as an emergent property of simple behavioral algorithms interacting with complex resource landscapes, and that relative density or sparsity of resources and the need to search can have profound consequences for mosquito populations' capacity to transmit pathogens.

The basic reproductive number for disease systems with multiple coupled heterogeneities

In mathematical epidemiology, a well-known formula describes the impact of heterogeneity on the basic reproductive number, R0, for situations in which transmission is separable and for which there is one source of variation in susceptibility and one source of variation in infectiousness. This formula is written in terms of the magnitudes of the heterogeneities, as quantified by their coefficients of variation, and the correlation between them. A natural question to ask is whether analogous results apply when there are multiple sources of variation in susceptibility and/or infectiousness. In this paper we demonstrate that with three or more coupled heterogeneities, R0 under separable transmission depends on details of the distribution of the heterogeneities in a way that is not seen in the well-known simpler situation. We provide explicit formulae for the cases of multivariate normal and multivariate log-normal distributions, showing that R0 can again be expressed in terms of the magnitudes of the heterogeneities and the pairwise correlations between them. The formulae, however, differ between the two multivariate distributions, demonstrating that no formula of this type applies generally when there are three or more coupled heterogeneities. We see that the results of the formulae are approximately equal when heterogeneities are relatively small and show that an earlier result in the literature (Koella, 1991) should be viewed in this light. We provide numerical illustrations of our results and discuss a setting in which coupled heterogeneities are likely to have a major impact on the value of R0. We also describe a rather surprising result: in a system with three heterogeneities, R0 can exhibit non-monotonic behavior with increasing levels of heterogeneity, in marked contrast to the familiar two heterogeneity setting in which R0 either increases or decreases with increasing heterogeneity.