An immune memory-structured SIS epidemiological model for hyperdiverse pathogens.

A hyperdiverse class of pathogens of humans and wildlife, including the malaria parasite Plasmodium falciparum, relies on multigene families to encode antigenic variation. As a result, high (asymptomatic) prevalence is observed despite high immunity in local populations under high-transmission settings. The vast diversity of "strains" and genes encoding this variation challenges the application of established models for the population dynamics of such infectious diseases. Agent-based models have been formulated to address theory on strain coexistence and structure, but their complexity can limit application to gain insights into population dynamics. Motivated by P. falciparum malaria, we develop an alternative formulation in the form of a structured susceptible-infected-susceptible population model in continuous time, where individuals are classified not only by age, as is standard, but also by the diversity of parasites they have been exposed to and retain in their specific immune memory. We analyze the population dynamics and bifurcation structure of this system of partial-differential equations, showing the existence of alternative steady states and an associated tipping point with transmission intensity. We attribute the critical transition to the positive feedback between parasite genetic diversity and force of infection. Basins of attraction show that intervention must drastically reduce diversity to prevent a rebound to high infection levels. Results emphasize the importance of explicitly considering pathogen diversity and associated specific immune memory in the population dynamics of hyperdiverse epidemiological systems. This statement is discussed in a more general context for ecological competition systems with hyperdiverse trait spaces.

Neutral vs. non-neutral genetic footprints of Plasmodium falciparum multiclonal infections.

At a time when effective tools for monitoring malaria control and eradication efforts are crucial, the increasing availability of molecular data motivates their application to epidemiology. The multiplicity of infection (MOI), defined as the number of genetically distinct parasite strains co-infecting a host, is one key epidemiological parameter for evaluating malaria interventions. Estimating MOI remains a challenge for high-transmission settings where individuals typically carry multiple co-occurring infections. Several quantitative approaches have been developed to estimate MOI, including two cost-effective ones relying on molecular data: i) THE REAL McCOIL method is based on putatively neutral single nucleotide polymorphism loci, and ii) the varcoding method is a fingerprinting approach that relies on the diversity and limited repertoire overlap of the var multigene family encoding the major Plasmodium falciparum blood-stage antigen PfEMP1 and is therefore under selection. In this study, we assess the robustness of the MOI estimates generated with these two approaches by simulating P. falciparum malaria dynamics under three transmission conditions using an extension of a previously developed stochastic agent-based model. We demonstrate that these approaches are complementary and best considered across distinct transmission intensities. While varcoding can underestimate MOI, it allows robust estimation, especially under high transmission where repertoire overlap is extremely limited from frequency-dependent selection. In contrast, THE REAL McCOIL often considerably overestimates MOI, but still provides reasonable estimates for low and moderate transmission. Regardless of transmission intensity, results for THE REAL McCOIL indicate that an inaccurate tail at high MOI values is generated, and that at high transmission, an apparently reasonable estimated MOI distribution can arise from some degree of compensation between overestimation and underestimation. As many countries pursue malaria elimination targets, defining the most suitable approach to estimate MOI based on sample size and local transmission intensity is highly recommended for monitoring the impact of intervention programs.

Quantifying asymptomatic infection and transmission of COVID-19 in New York City using observed cases, serology, and testing capacity.

The contributions of asymptomatic infections to herd immunity and community transmission are key to the resurgence and control of COVID-19, but are difficult to estimate using current models that ignore changes in testing capacity. Using a model that incorporates daily testing information fit to the case and serology data from New York City, we show that the proportion of symptomatic cases is low, ranging from 13 to 18%, and that the reproductive number may be larger than often assumed. Asymptomatic infections contribute substantially to herd immunity, and to community transmission together with presymptomatic ones. If asymptomatic infections transmit at similar rates as symptomatic ones, the overall reproductive number across all classes is larger than often assumed, with estimates ranging from 3.2 to 4.4. If they transmit poorly, then symptomatic cases have a larger reproductive number ranging from 3.9 to 8.1. Even in this regime, presymptomatic and asymptomatic cases together comprise at least 50% of the force of infection at the outbreak peak. We find no regimes in which all infection subpopulations have reproductive numbers lower than three. These findings elucidate the uncertainty that current case and serology data cannot resolve, despite consideration of different model structures. They also emphasize how temporal data on testing can reduce and better define this uncertainty, as we move forward through longer surveillance and second epidemic waves. Complementary information is required to determine the transmissibility of asymptomatic cases, which we discuss. Regardless, current assumptions about the basic reproductive number of severe acute respiratory syndrome coronavirus 2 (SARS-Cov-2) should be reconsidered.

Humidity - The overlooked variable in the thermal biology of mosquito-borne disease.

Vector-borne diseases cause significant financial and human loss, with billions of dollars spent on control. Arthropod vectors experience a complex suite of environmental factors that affect fitness, population growth and species interactions across multiple spatial and temporal scales. Temperature and water availability are two of the most important abiotic variables influencing their distributions and abundances. While extensive research on temperature exists, the influence of humidity on vector and pathogen parameters affecting disease dynamics are less understood. Humidity is often underemphasized, and when considered, is often treated as independent of temperature even though desiccation likely contributes to declines in trait performance at warmer temperatures. This Perspectives explores how humidity shapes the thermal performance of mosquito-borne pathogen transmission. We summarize what is known about its effects and propose a conceptual model for how temperature and humidity interact to shape the range of temperatures across which mosquitoes persist and achieve high transmission potential. We discuss how failing to account for these interactions hinders efforts to forecast transmission dynamics and respond to epidemics of mosquito-borne infections. We outline future research areas that will ground the effects of humidity on the thermal biology of pathogen transmission in a theoretical and empirical framework to improve spatial and temporal prediction of vector-borne pathogen transmission.

Competition for hosts modulates vast antigenic diversity to generate persistent strain structure in Plasmodium falciparum.

In their competition for hosts, parasites with antigens that are novel to the host immune system will be at a competitive advantage. The resulting frequency-dependent selection can structure parasite populations into strains of limited genetic overlap. For the causative agent of malaria, Plasmodium falciparum, the high recombination rates and associated vast diversity of its highly antigenic and multicopy var genes preclude such clear clustering in endemic regions. This undermines the definition of strains as specific, temporally persisting gene variant combinations. We use temporal multilayer networks to analyze the genetic similarity of parasites in both simulated data and in an extensively and longitudinally sampled population in Ghana. When viewed over time, populations are structured into modules (i.e., groups) of parasite genomes whose var gene combinations are more similar within than between the modules and whose persistence is much longer than that of the individual genomes that compose them. Comparison to neutral models that retain parasite population dynamics but lack competition reveals that the selection imposed by host immunity promotes the persistence of these modules. The modular structure is, in turn, associated with a slower acquisition of immunity by individual hosts. Modules thus represent dynamically generated niches in host immune space, which can be interpreted as strains. Negative frequency-dependent selection therefore shapes the organization of the var diversity into parasite genomes, leaving a persistence signature over ecological time scales. Multilayer networks extend the scope of phylodynamics analyses by allowing quantification of temporal genetic structure in organisms that generate variation via recombination or other non-bifurcating processes. A strain structure similar to the one described here should apply to other pathogens with large antigenic spaces that evolve via recombination. For malaria, the temporal modular structure should enable the formulation of tractable epidemiological models that account for parasite antigenic diversity and its influence on intervention outcomes.

Development, environmental degradation, and disease spread in the Brazilian Amazon.

The Amazon is Brazil's greatest natural resource and invaluable to the rest of the world as a buffer against climate change. The recent election of Brazil's president brought disputes over development plans for the region back into the spotlight. Historically, the development model for the Amazon has focused on exploitation of natural resources, resulting in environmental degradation, particularly deforestation. Although considerable attention has focused on the long-term global cost of "losing the Amazon," too little attention has focused on the emergence and reemergence of vector-borne diseases that directly impact the local population, with spillover effects to other neighboring areas. We discuss the impact of Amazon development models on human health, with a focus on vector-borne disease risk. We outline policy actions that could mitigate these negative impacts while creating opportunities for environmentally sensitive economic activities.

An antigenic diversification threshold for falciparum malaria transmission at high endemicity.

In malaria and several other important infectious diseases, high prevalence occurs concomitantly with incomplete immunity. This apparent paradox poses major challenges to malaria elimination in highly endemic regions, where asymptomatic Plasmodium falciparum infections are present across all age classes creating a large reservoir that maintains transmission. This reservoir is in turn enabled by extreme antigenic diversity of the parasite and turnover of new variants. We present here the concept of a threshold in local pathogen diversification that defines a sharp transition in transmission intensity below which new antigen-encoding genes generated by either recombination or migration cannot establish. Transmission still occurs below this threshold, but diversity of these genes can neither accumulate nor recover from interventions that further reduce it. An analytical expectation for this threshold is derived and compared to numerical results from a stochastic individual-based model of malaria transmission that incorporates the major antigen-encoding multigene family known as var. This threshold corresponds to an "innovation" number we call Rdiv; it is different from, and complementary to, the one defined by the classic basic reproductive number of infectious diseases, R0, which does not readily is better apply under large and dynamic strain diversity. This new threshold concept can be exploited for effective malaria control and applied more broadly to other pathogens with large multilocus antigenic diversity.

The impact of indoor residual spraying on Plasmodium falciparum microsatellite variation in an area of high seasonal malaria transmission in Ghana, West Africa.

Here, we report the first population genetic study to examine the impact of indoor residual spraying (IRS) on Plasmodium falciparum in humans. This study was conducted in an area of high seasonal malaria transmission in Bongo District, Ghana. IRS was implemented during the dry season (November-May) in three consecutive years between 2013 and 2015 to reduce transmission and attempt to bottleneck the parasite population in humans towards lower diversity with greater linkage disequilibrium. The study was done against a background of widespread use of long-lasting insecticidal nets, typical for contemporary malaria control in West Africa. Microsatellite genotyping with 10 loci was used to construct 392 P. falciparum multilocus infection haplotypes collected from two age-stratified cross-sectional surveys at the end of the wet seasons pre- and post-IRS. Three-rounds of IRS, under operational conditions, led to a >90% reduction in transmission intensity and a 35.7% reduction in the P. falciparum prevalence (p < .001). Despite these declines, population genetic analysis of the infection haplotypes revealed no dramatic changes with only a slight, but significant increase in genetic diversity (He : pre-IRS = 0.79 vs. post-IRS = 0.81, p = .048). Reduced relatedness of the parasite population (p < .001) was observed post-IRS, probably due to decreased opportunities for outcrossing. Spatiotemporal genetic differentiation between the pre- and post-IRS surveys (D = 0.0329 [95% CI: 0.0209 - 0.0473], p = .034) was identified. These data provide a genetic explanation for the resilience of P. falciparum to short-term IRS programmes in high-transmission settings in sub-Saharan Africa.

COVID-Clarity demands unification of health and environmental policy.

Spillover of novel pathogens from wildlife to people, such as the virus responsible for the COVID-19 pandemic, is increasing and this trend is most strongly associated with tropical deforestation driven by agricultural expansion. This same process is eroding natural capital, reducing forest-associated health co-benefits, and accelerating climate change. Protecting and promoting tropical forests is one of the most immediate steps we can take to simultaneously mitigate climate change while reducing the risk of future pandemics; however, success in this undertaking will require greater connectivity of policy initiatives from local to global, as well as unification of health and environmental policy.

Tube Well Use as Protection Against Rotavirus Infection During the Monsoons in an Urban Setting.

Rotavirus, a diarrheal pathogen spread via fecal-oral transmission, is typically characterized by a winter incidence peak in most countries. Unlike for cholera and other waterborne infections, the role of sanitation and socioeconomic factors on the spatial variation of rotavirus seasonality remains unclear. In the current study, we analyzed their association with rotavirus seasonality, specifically the odds of monsoon cases, across 46 locations from 2001 to 2012 in Dhaka. Drinking water from tube wells, compared to other sources, has a clear protective effect against cases during the monsoon, when flooding and water contamination are more likely. This finding supports a significant environmental component of transmission.

Evidence of strain structure in Plasmodium falciparum var gene repertoires in children from Gabon, West Africa.

Existing theory on competition for hosts between pathogen strains has proposed that immune selection can lead to the maintenance of strain structure consisting of discrete, weakly overlapping antigenic repertoires. This prediction of strain theory has conceptual overlap with fundamental ideas in ecology on niche partitioning and limiting similarity between coexisting species in an ecosystem, which oppose the hypothesis of neutral coexistence. For Plasmodium falciparum, strain theory has been specifically proposed in relation to the major surface antigen of the blood stage, known as PfEMP1 and encoded by the multicopy multigene family known as the var genes. Deep sampling of the DBLα domain of var genes in the local population of Bakoumba, West Africa, was completed to define whether patterns of repertoire overlap support a role of immune selection under the opposing force of high outcrossing, a characteristic of areas of intense malaria transmission. Using a 454 high-throughput sequencing protocol, we report extremely high diversity of the DBLα domain and a large parasite population with DBLα repertoires structured into nonrandom patterns of overlap. Such population structure, significant for the high diversity of var genes that compose it at a local level, supports the existence of "strains" characterized by distinct var gene repertoires. Nonneutral, frequency-dependent competition would be at play and could underlie these patterns. With a computational experiment that simulates an intervention similar to mass drug administration, we argue that the observed repertoire structure matters for the antigenic var diversity of the parasite population remaining after intervention.

Identifying functional groups among the diverse, recombining antigenic var genes of the malaria parasite Plasmodium falciparum from a local community in Ghana.

A challenge in studying diverse multi-copy gene families is deciphering distinct functional types within immense sequence variation. Functional changes can in some cases be tracked through the evolutionary history of a gene family; however phylogenetic approaches are not possible in cases where gene families diversify primarily by recombination. We take a network theoretical approach to functionally classify the highly recombining var antigenic gene family of the malaria parasite Plasmodium falciparum. We sample var DBLα sequence types from a local population in Ghana, and classify 9,276 of these variants into just 48 functional types. Our approach is to first decompose each sequence type into its constituent, recombining parts; we then use a stochastic block model to identify functional groups among the parts; finally, we classify the sequence types based on which functional groups they contain. This method for functional classification does not rely on an inferred phylogenetic history, nor does it rely on inferring function based on conserved sequence features. Instead, it infers functional similarity among recombining parts based on the sharing of similar co-occurrence interactions with other parts. This method can therefore group sequences that have undetectable sequence homology or even distinct origination. Describing these 48 var functional types allows us to simplify the antigenic diversity within our dataset by over two orders of magnitude. We consider how the var functional types are distributed in isolates, and find a nonrandom pattern reflecting that common var functional types are non-randomly distinct from one another in terms of their functional composition. The coarse-graining of var gene diversity into biologically meaningful functional groups has important implications for understanding the disease ecology and evolution of this system, as well as for designing effective epidemiological monitoring and intervention.

Pseudomonas edaphica sp. nov., isolated from rhizospheric soil of Cistus ladanifer L. in Spain.

During a study on biodiversity of bacteria inhabiting rhizospheric soil of rockrose (Cistus ladanifer L.), we isolated a strain coded RD25T in a soil from Northern Spain. The 16S rRNA gene sequence showed 99.5 % identity with respect to the closest related species Pseudomonas brenneri DSM15294T, and 99.4 % with respect to P. paralactis WS4672T. The following related Pseudomonas species showed 99.3 % or less identity, and therefore RD25T was classified within genus Pseudomonas. The phylogenetic analysis of 16S rRNA and the housekeeping genes rpoB, rpoD and gyrB suggested that this strain could be a novel species. The strain RD25T has several polar-subpolar flagella. It can grow at 36 °C, at 0-6 % NaCl concentration and a range of pH 5-9. Positive for arginine dihydrolase and urease production, and negative for reduction of nitrate. The strain is catalase and oxidase positive. Major fatty acids are C16 : 1 ω7c / C16 : 1 ω6c in summed feature 3, C16 : 0, and C18 : 1 ω7c / C18 : 1 ω6c in summed feature 8. The respiratory ubiquinone is Q9. The DNA G+C content was 59.9 mol%. The digital DNA-DNA hybridisation average values (dDDH) ranged between 30-61.2 % relatedness and the ANIb values ranged between 93.9-80.5 % with respect to the type strains of the closely related species. Therefore, the genotypic, genomic, phenotypic and chemotaxonomic data support the classification of strain RD25 as a novel species of genus Pseudomonas, for which the name P. edaphica sp. nov. is proposed. The type strain is RD25T (=LMG 30152T=CECT 9373T).

Differential and enhanced response to climate forcing in diarrheal disease due to rotavirus across a megacity of the developing world.

The role of climate forcing in the population dynamics of infectious diseases has typically been revealed via retrospective analyses of incidence records aggregated across space and, in particular, over whole cities. Here, we focus on the transmission dynamics of rotavirus, the main diarrheal disease in infants and young children, within the megacity of Dhaka, Bangladesh. We identify two zones, the densely urbanized core and the more rural periphery, that respond differentially to flooding. Moreover, disease seasonality differs substantially between these regions, spanning variation comparable to the variation from tropical to temperate regions. By combining process-based models with an extensive disease surveillance record, we show that the response to climate forcing is mainly seasonal in the core, where a more endemic transmission resulting from an asymptomatic reservoir facilitates the response to the monsoons. The force of infection in this monsoon peak can be an order of magnitude larger than the force of infection in the more epidemic periphery, which exhibits little or no postmonsoon outbreak in a pattern typical of nearby rural areas. A typically smaller peak during the monsoon season nevertheless shows sensitivity to interannual variability in flooding. High human density in the core is one explanation for enhanced transmission during troughs and an associated seasonal monsoon response in this diarrheal disease, which unlike cholera, has not been widely viewed as climate-sensitive. Spatial demographic, socioeconomic, and environmental heterogeneity can create reservoirs of infection and enhance the sensitivity of disease systems to climate forcing, especially in the populated cities of the developing world.

Mosquito-borne transmission in urban landscapes: the missing link between vector abundance and human density.

With escalating urbanization, the environmental, demographic, and socio-economic heterogeneity of urban landscapes poses a challenge to mathematical models for the transmission of vector-borne infections. Classical coupled vector-human models typically assume that mosquito abundance is either independent from, or proportional to, human population density, implying a decreasing force of infection, or per capita infection rate with host number. We question these assumptions by introducing an explicit dependence between host and vector densities through different recruitment functions, whose dynamical consequences we examine in a modified model formulation. Contrasting patterns in the force of infection are demonstrated, including in particular increasing trends when recruitment grows sufficiently fast with human density. Interaction of these patterns with seasonality in temperature can give rise to pronounced differences in timing, relative peak sizes, and duration of epidemics. These proposed dependencies explain empirical dengue risk patterns observed in the city of Delhi where socio-economic status has an impact on both human and mosquito densities. These observed risk trends with host density are inconsistent with current standard models. A better understanding of the connection between vector recruitment and host density is needed to address the population dynamics of mosquito-transmitted infections in urban landscapes.

Understanding the role of parasites in food webs using the group model.

Parasites are ubiquitous and have been shown to influence macroscopic measures of ecological network structure, such as connectance and robustness, as well as local structure, such as subgraph frequencies. Nevertheless, they are often under-represented in ecological studies due to their small size and often complex life cycles. We consider whether or not parasites play structurally unique roles in ecological networks; that is, can we distinguish parasites from other species using network structure alone? We partition the species in a community statistically using the group model, and we test whether or not parasites tend to cluster in their own groups, using a measure of "imbalance." We find that parasites form highly imbalanced groups, and that concomitant predation, in which a predator consumes a prey and its parasites, but not the number of interactions, improves the group model's ability to distinguish parasites from non-parasites. This work demonstrates that parasites and non-parasites interact in networks in statistically distinct ways, and that these differences are partly, but not entirely, due to the existence of concomitant predation.

Synergistic and antagonistic interactions between bednets and vaccines in the control of malaria.

It is extremely likely that the malaria vaccines currently in development will be used in conjunction with treated bednets and other forms of malaria control. The interaction of different intervention methods is at present poorly understood in a disease such as malaria where immunity is more complex than for other pathogens that have been successfully controlled by vaccination. Here we develop a general mathematical model of malaria transmission to examine the interaction between vaccination and bednets. Counterintuitively, we find that the frailty of malaria immunity will potentially cause both synergistic and antagonistic interactions between vaccination and the use of bednets. We explore the conditions that create these tensions, and outline strategies that minimize their detrimental impact. Our analysis specifically considers the three leading vaccine classes currently in development: preerythrocytic (PEV), blood stage (BSV), and transmission blocking (TBV). We find that the combination of BSV with treated bednets can lead to increased morbidity with no added value in terms of elimination; the interaction is clearly antagonistic. In contrast, there is strong synergy between PEV and treated bednets that may facilitate elimination, although transient stages are likely to increase morbidity. The combination of TBV with treated bednets is synergistic, lowering both morbidity and elimination thresholds. Our results suggest that vaccines will not provide a straightforward solution to malaria control, and that future programs need to consider the synergistic and antagonistic interactions between vaccines and treated bednets.

Paenibacillus tritici sp. nov., isolated from wheat roots.

A bacterial strain designated RTAE36T was isolated from wheat roots in northern Spain. Phylogenetic analyses based on 16S rRNA gene sequence placed the isolate into the genus Paenibacillus with its closest relative being Paenibacillus borealis DSM 13188T with 97.7 % sequence similarity. Cells of the isolate were facultatively anaerobic, Gram-stain-positive, motile and sporulating rods. Catalase and oxidase were positive. Gelatin, casein and starch were not hydrolysed. Growth was supported by many carbohydrates and organic acids as carbon sources. MK-7 was the only menaquinone detected, and anteiso-C15 : 0, C16 : 0, iso-C14 : 0 and iso-C16 : 0 were the major fatty acids. The polar lipids profile consisted of diphosphatidylglycerol, phosphatidylglycerol, phosphatidylethanolamine, one unidentified aminolipid, two unidentified phospholipids, three unidentified phosphoaminolipids, one unidentified glycolipid and one unidentified lipid. meso-Diaminopimelic acid was detected in the cell-wall peptidoglycan. Strains RTAE36T and P. borealis DSM 13188T had an mean DNA-DNA relatedness of 39 % and differed in several phenotypic and chemotaxonomic characteristics, confirming that strain RTAE36T should be considered as a representative of a novel species of the genus Paenibacillus, for which the name Paenibacillus tritici sp. nov. is proposed. The type strain is RTAE36T (=LMG 29502T=CECT 9125T).

Brevundimonas canariensis sp. nov., isolated from roots of Triticum aestivum.

A bacterial strain designated GTAE24T was isolated from a root of wheat growing in soil from the Canary Islands, Spain. Phylogenetic analyses based on 16S rRNA gene sequences placed the isolate in the genus Brevundimonas with Brevundimonas abyssalisTAR-001T as its closest relative at 99.4 % similarity. DNA-DNA hybridization studies showed an average of 38 % relatedness between strain GTAE24T and the type strain of B. abyssalis. Cells were Gram-stain-negative and motile by polar flagella. The strain was positive for oxidase and weakly positive for catalase. Gelatin, starch and casein were not hydrolysed. Growth was supported by many carbohydrates and organic acids as carbon source. Ubiquinone Q-10 was the predominant isoprenoid quinone and C18 : 1ω7c/C18 : 1ω6c (summed feature 8) and C16 : 0 were the major fatty acids. The major polar lipids were phosphatidylglycerol, 1,2-di-O-acyl-3-O-[d-glucopyranosyl-(1,4)-α-d-glucopyranuronosyl] glycerol, 1,2-diacyl-3-O-[6'-phosphatidyl-α-d-glucopyranosyl] glycerol, 1,2-di-O-acyl-3-O-α-d-glucopyranosyl glycerol, and 1,2-di-O-acyl-3-O-α-d-glucopyranuronosyl glycerol. The DNA G+C content was 63.9 mol%. Phylogenetic, chemotaxonomic and phenotypic analyses showed that strain GTAE24T should be considered as representing a novel species of the genus Brevundimonas, for which the name Brevundimonas canariensis sp. nov. is proposed. The type strain is GTAE24T (=LMG 29500T=CECT 9126T).

Climate-driven endemic cholera is modulated by human mobility in a megacity.

Although a differential sensitivity of cholera dynamics to climate variability has been reported in the spatially heterogeneous megacity of Dhaka, Bangladesh, the specific patterns of spread of the resulting risk within the city remain unclear. We build on an established probabilistic spatial model to investigate the importance and role of human mobility in modulating spatial cholera transmission. Mobility fluxes were inferred using a straightforward and generalizable methodology that relies on mapping population density based on a high resolution urban footprint product, and a parameter-free human mobility model. In accordance with previous findings, we highlight the higher sensitivity to the El Niño Southern Oscillation (ENSO) in the highly populated urban center than in the more rural periphery. More significantly, our results show that cholera risk is largely transmitted from the climate-sensitive core to the periphery of the city, with implications for the planning of control efforts. In addition, including human mobility improves the outbreak prediction performance of the model with an 11 month lead. The interplay between climatic and human mobility factors in cholera transmission is discussed from the perspective of the rapid growth of megacities across the developing world.