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arxiv: 2605.21787 · v1 · pith:6QEXNPVJnew · submitted 2026-05-20 · 🧬 q-bio.PE

Drivers of Transient Dynamics and Persistence in Dengue: Insights from Sensitivity and Stochastic Modeling

Cesar Alberto Rosales-Alcantar , Marcos A. Capistr\'an This is my paper

Pith reviewed 2026-05-22 07:21 UTC · model grok-4.3

classification 🧬 q-bio.PE
keywords denguesensitivity analysisstochastic modelvector-host dynamicsvertical transmissionepidemic persistencewaning immunitySobol indices
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The pith

Mosquito-to-human ratio and recovery rate top the sensitivity ranking in a dengue model.

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

The paper builds a stochastic model of dengue spread between people and mosquitoes that incorporates waning human immunity, outside introductions of the virus, and transmission from mother mosquitoes to their eggs. It applies sensitivity analysis to epidemic measures such as peak size and duration, then ranks how much each parameter affects those outcomes. The analysis shows that the number of mosquitoes per person and the speed at which infected people stop being infectious exert the strongest influence, stronger even than the rate of bites between people and mosquitoes. This ordering points toward control tactics that shield sick individuals from mosquitoes during outbreaks rather than blanket reductions in contacts. The model further indicates that vertical transmission helps the virus persist between seasons by lowering the threshold for long-term presence and by creating egg-based reservoirs that can restart outbreaks.

Core claim

The paper establishes that in its stochastic vector-host dengue model the vector-host population ratio and host recovery rate carry the largest first-order and total sensitivity indices for epidemic summary statistics, outranking contact rates and thereby directing seasonal control toward protecting infectious hosts from mosquito bites. Vertical transmission reduces the persistence threshold, low spatial coupling raises infectious endemic equilibria, and host-vector covariance at the endemic equilibrium remains asynchronous across the contact-rate plane, revealing two niches per strain and a fluctuation-driven mechanism for high vertical transmission that sustains viral reservoirs between .

What carries the argument

Multivariate Sobol sensitivity analysis performed on epidemic summary statistics generated by the stochastic vector-host model that includes waning immunity, exogenous infection, and vertical transmission.

If this is right

  • Seasonal control programs should emphasize measures that keep mosquitoes from biting people who already have dengue.
  • Vertical transmission from adult mosquitoes to eggs lowers the population threshold needed for the virus to remain endemic.
  • Reduced movement between human populations raises the number of infectious individuals at equilibrium.
  • Asynchronous host-vector fluctuations at equilibrium create separate niches that allow multiple strains to coexist and support viral persistence through egg reservoirs.

Where Pith is reading between the lines

These are editorial extensions of the paper, not claims the author makes directly.

  • The same sensitivity ordering could appear in models of other mosquito-borne viruses such as Zika or chikungunya that share the same vectors.
  • Collecting local data on mosquito densities and average recovery times might allow early prediction of which neighborhoods will see larger seasonal outbreaks.
  • Adding realistic urban movement patterns to the model could test whether the current ranking of controls still holds in densely connected cities.

Load-bearing premise

The chosen stochastic model with waning immunity, outside virus introductions, and vertical transmission faithfully represents the main processes that govern real dengue spread and persistence.

What would settle it

Field data showing no systematic link between measured mosquito-to-human ratios and observed dengue case counts or outbreak sizes across multiple sites would contradict the sensitivity ranking.

Figures

Figures reproduced from arXiv: 2605.21787 by Cesar Alberto Rosales-Alcantar, Marcos A. Capistr\'an.

Figure 1
Figure 1. Figure 1: Dengue transmission model with vertical transmission in vectors. The diagram shows a compartmental model of dengue transmission between humans and mosquitoes. Humans are divided into susceptible (Sh), infectious (Ih), and recovered (Rh) classes. Mosquitoes are divided into susceptible (Sv) and infectious (Iv) classes. Susceptible humans are infected at rate λh through bites from infectious mosquitoes. They… view at source ↗
Figure 2
Figure 2. Figure 2: Mean first–order (S1, blue) and total–order (ST , orange) Sobol sensitivity indices of the dengue model parameters, averaged across outbreak summary statistics (peak incidence, area under the curve, stan￾dard deviation, and minimum incidence). The vector–to–host ratio C is the dominant parameter, exhibiting the largest total–order sensitivity index and indicating a strong influence that includes interactio… view at source ↗
Figure 5
Figure 5. Figure 5: All simulations were conducted while holding the deterministic reproduction number fixed at [PITH_FULL_IMAGE:figures/full_fig_p014_5.png] view at source ↗
Figure 3
Figure 3. Figure 3: First-order Sobol indices (S1) of dengue model parameters are shown for each outbreak statistic: maximum, minimum, standard deviation, and area under the curve (AUC) of human (Ih) and vector (Iv) infectious fractions. The vector-to-host ratio C strongly affects maxima and minima in both populations, while the human recovery rate γh dominates the variance and AUC of human infections. Vertical transmission p… view at source ↗
Figure 4
Figure 4. Figure 4: Basic reproduction number and variance of infectious classes at the endemic equilibrium as func [PITH_FULL_IMAGE:figures/full_fig_p017_4.png] view at source ↗
Figure 5
Figure 5. Figure 5: Gillespie realizations of the dengue transmission model for two parameter pairs lying on the same [PITH_FULL_IMAGE:figures/full_fig_p018_5.png] view at source ↗
read the original abstract

We investigate how key epidemiological parameters shape both seasonal epidemics and the persistence of dengue transmission. Our findings confirm known mechanistic drivers of epidemic variability and introduce a ranking of parameter importance in our dengue model, which in turn informs the prioritization of public health policies. We propose a stochastic vector-host model with waning immunity, exogenous infection, and vertical transmission. To assess parameter influence, we first qualitatively analyze the macroscopic model. We then perform a multivariate Sobol sensitivity analysis of epidemic summary statistics, and examine the variance of the endemic equilibrium as a function of model parameters. We show that the macroscopic model is well posed, vertical transmission lowers the threshold for persistence, and low spatial coupling increases infectious endemic equilibria. The vector-host population ratio and host recovery rate have the largest first-order and total sensitivity indices, surpassing the contact rates; this implies that control measures during seasonal dengue should prioritize protecting infectious hosts from mosquito bites. Finally, we show that the covariance of hosts and vectors at the endemic equilibrium is asynchronous in the contact-rate plane. This robust pattern has epidemiological, ecological and evolutive interpretations. A dengue strain has two niches to exploit during the endemic regime, and coexisting strain have two niches each. Moreover, large fluctuations in a given strain during the endemic regime provide a mechanistic explanation for high vertical transmission, enabling viral reservoirs that can hatch and trigger outbreaks in the following season. We argue that our model and results can be adapted to address specific public health questions to guide dengue control using field data.

Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, simulated authors' rebuttal, and a circularity audit. Tearing a paper down is the easy half of reading it; the pith above is the substance, this is the friction.

Referee Report

1 major / 2 minor

Summary. The manuscript develops a stochastic vector-host model for dengue incorporating waning immunity, exogenous infection, and vertical transmission. It qualitatively analyzes the macroscopic model, conducts multivariate Sobol sensitivity analysis on epidemic summary statistics, and examines variance of the endemic equilibrium as a function of parameters. Key results include well-posedness of the macroscopic model, lowering of the persistence threshold by vertical transmission, increase in infectious endemic equilibria with low spatial coupling, dominance of vector-host population ratio and host recovery rate in first-order and total Sobol indices over contact rates (implying prioritization of protecting infectious hosts from mosquito bites for seasonal control), and asynchronous host-vector covariance at endemic equilibrium with interpretations for strain niches, coexistence, and vertical transmission as a reservoir mechanism.

Significance. If the sensitivity rankings prove robust and the mapping from parameter influence to intervention effect sizes is clarified, the work could usefully inform dengue control prioritization by elevating vector-host ratios and recovery rates relative to contact rates. The stochastic formulation, analysis of transient dynamics, and persistence thresholds add mechanistic insight beyond deterministic approaches. The covariance findings and niche interpretations provide ecological context that may aid understanding of strain persistence and outbreak triggers.

major comments (1)
  1. [Abstract and sensitivity results] Abstract (policy implication paragraph): the claim that dominance of vector-host ratio and host recovery rate in Sobol indices implies control should prioritize protecting infectious hosts from mosquito bites is not supported by the presented analysis. Bite protection primarily modulates contact/transmission rates (shown to have lower indices), while recovery rate is a fixed biological parameter not directly altered by such interventions; no explicit mapping from sensitivity indices to intervention effect sizes or alternative control levers (e.g., on vector density) is provided to bridge this gap.
minor comments (2)
  1. [Model description] Model formulation section: provide the full set of stochastic differential equations or transition rates, including explicit terms for waning immunity, exogenous infection, and vertical transmission, to support reproducibility and verification of the macroscopic analysis.
  2. [Sensitivity analysis] Sensitivity analysis section: specify the exact epidemic summary statistics used for Sobol indices, the sampling ranges for parameters, and any convergence diagnostics for the indices.

Simulated Author's Rebuttal

1 responses · 0 unresolved

Thank you for the detailed and constructive review of our manuscript. We appreciate the referee's positive assessment of the stochastic modeling approach, sensitivity analysis, and potential implications for dengue control. We address the major comment on the abstract below and will revise the manuscript accordingly to ensure all claims are precisely supported by the analysis.

read point-by-point responses

  1. Referee: [Abstract and sensitivity results] Abstract (policy implication paragraph): the claim that dominance of vector-host ratio and host recovery rate in Sobol indices implies control should prioritize protecting infectious hosts from mosquito bites is not supported by the presented analysis. Bite protection primarily modulates contact/transmission rates (shown to have lower indices), while recovery rate is a fixed biological parameter not directly altered by such interventions; no explicit mapping from sensitivity indices to intervention effect sizes or alternative control levers (e.g., on vector density) is provided to bridge this gap.

    Authors: We agree that the original phrasing in the abstract draws an implication that is not directly supported by the presented results. The Sobol analysis shows high sensitivity for the vector-host ratio (suggesting leverage through vector density reduction) and host recovery rate, but bite protection interventions would indeed act primarily through contact or transmission rates, which rank lower. Recovery rate is a fixed biological parameter not explicitly tied to modeled interventions. No quantitative mapping from indices to effect sizes was performed. In the revised version, we will remove the specific claim about prioritizing protection of infectious hosts from mosquito bites. The abstract will instead report the sensitivity rankings and note that the vector-host ratio's prominence may inform vector control strategies, while clarifying that direct links to intervention effect sizes require additional analysis beyond the current scope. revision: yes

Circularity Check

0 steps flagged

No significant circularity; sensitivity rankings are computed outputs

full rationale

The paper proposes an explicit stochastic vector-host model with waning immunity, exogenous infection and vertical transmission, then applies qualitative macroscopic analysis followed by multivariate Sobol sensitivity on epidemic summary statistics and endemic-equilibrium variance. The reported ranking (vector-host ratio and recovery rate dominating contact rates) is produced by these numerical procedures on the chosen parameter set and is not equivalent to any model input by construction. No self-definitional equations, fitted parameters renamed as predictions, or load-bearing self-citations appear in the derivation chain. The control implication is an interpretive step downstream of the computed indices rather than a tautological reduction.

Axiom & Free-Parameter Ledger

0 free parameters · 0 axioms · 0 invented entities

The abstract does not list explicit free parameters or axioms, but the model construction itself rests on standard compartmental assumptions plus the addition of waning immunity, vertical transmission, and exogenous infection; without the full text these cannot be audited.

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Reference graph

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