SciCompMod · HenrZu · Oct 7, 2025 · Aug 1, 2025 · Aug 1, 2025 · Aug 5, 2025
diff --git a/cpp/examples/d_abm.cpp b/cpp/examples/d_abm.cpp
@@ -1,5 +1,5 @@
 /*
-* Copyright (C) 2020-2024 German Aerospace Center (DLR-SC)
+* Copyright (C) 2020-2025 MEmilio
 *
 * Authors: Julia Bicker, René Schmieding
 *

diff --git a/cpp/examples/graph_abm.cpp b/cpp/examples/graph_abm.cpp
@@ -1,5 +1,5 @@
 /*
-* Copyright (C) 2020-2024 MEmilio
+* Copyright (C) 2020-2025 MEmilio
 *
 * Authors: Julia Bicker
 *

diff --git a/cpp/examples/smm.cpp b/cpp/examples/smm.cpp
@@ -1,5 +1,5 @@
 /*
-* Copyright (C) 2020-2024 German Aerospace Center (DLR-SC)
+* Copyright (C) 2020-2025 MEmilio
 *
 * Authors: Julia Bicker, René Schmieding
 *

diff --git a/cpp/memilio/geography/regions.h b/cpp/memilio/geography/regions.h
@@ -38,7 +38,7 @@ namespace mio
 namespace regions
 {
 
-/// @biref Index for enumerating subregions (cities, counties, etc.) of the modelled area.
+/// @brief Index for enumerating subregions (cities, counties, etc.) of the modelled area.
 struct Region : public mio::Index<Region> {
     Region(const size_t num_regions)
         : mio::Index<Region>(num_regions)

diff --git a/cpp/models/d_abm/model.cpp b/cpp/models/d_abm/model.cpp
@@ -1,5 +1,5 @@
 /*
-* Copyright (C) 2020-2025 German Aerospace Center (DLR-SC)
+* Copyright (C) 2020-2025 MEmilio
 *
 * Authors: René Schmieding
 *

diff --git a/cpp/models/d_abm/model.h b/cpp/models/d_abm/model.h
@@ -1,5 +1,5 @@
 /*
-* Copyright (C) 2020-2025 German Aerospace Center (DLR-SC)
+* Copyright (C) 2020-2025 MEmilio
 *
 * Authors: René Schmieding, Julia Bicker
 *

diff --git a/cpp/models/d_abm/parameters.h b/cpp/models/d_abm/parameters.h
@@ -1,5 +1,5 @@
 /*
-* Copyright (C) 2020-2024 German Aerospace Center (DLR-SC)
+* Copyright (C) 2020-2025 MEmilio
 *
 * Authors: René Schmieding, Julia Bicker
 *

diff --git a/cpp/models/d_abm/quad_well.h b/cpp/models/d_abm/quad_well.h
@@ -1,5 +1,5 @@
 /* 
-* Copyright (C) 2020-2025 German Aerospace Center (DLR-SC)
+* Copyright (C) 2020-2025 MEmilio
 *
 * Authors: René Schmieding, Julia Bicker
 *

diff --git a/cpp/models/d_abm/simulation.cpp b/cpp/models/d_abm/simulation.cpp
@@ -1,5 +1,5 @@
 /*
-* Copyright (C) 2020-2024 MEmilio
+* Copyright (C) 2020-2025 MEmilio
 *
 * Authors: René Schmieding, Julia Bicker
 *

diff --git a/cpp/models/d_abm/simulation.h b/cpp/models/d_abm/simulation.h
@@ -1,5 +1,5 @@
 /*
-* Copyright (C) 2020-2025 German Aerospace Center (DLR-SC)
+* Copyright (C) 2020-2025 MEmilio
 *
 * Authors: René Schmieding, Julia Bicker
 *

diff --git a/cpp/models/d_abm/single_well.h b/cpp/models/d_abm/single_well.h
@@ -1,5 +1,5 @@
 /* 
-* Copyright (C) 2020-2025 German Aerospace Center (DLR-SC)
+* Copyright (C) 2020-2025 MEmilio
 *
 * Authors: Julia Bicker, René Schmieding
 *

diff --git a/cpp/models/graph_abm/graph_abm_mobility.cpp b/cpp/models/graph_abm/graph_abm_mobility.cpp
@@ -1,5 +1,5 @@
 /*
-* Copyright (C) 2020-2024 MEmilio
+* Copyright (C) 2020-2025 MEmilio
 *
 * Authors: Julia Bicker
 *

diff --git a/cpp/models/graph_abm/graph_abm_mobility.h b/cpp/models/graph_abm/graph_abm_mobility.h
@@ -1,5 +1,5 @@
 /*
-* Copyright (C) 2020-2024 MEmilio
+* Copyright (C) 2020-2025 MEmilio
 *
 * Authors: Julia Bicker
 *

diff --git a/cpp/models/graph_abm/graph_abmodel.h b/cpp/models/graph_abm/graph_abmodel.h
@@ -1,5 +1,5 @@
 /*
-* Copyright (C) 2020-2024 MEmilio
+* Copyright (C) 2020-2025 MEmilio
 *
 * Authors: Julia Bicker
 *

diff --git a/cpp/models/hybrid/temporal_hybrid_model.cpp b/cpp/models/hybrid/temporal_hybrid_model.cpp
@@ -1,5 +1,5 @@
 /* 
-* Copyright (C) 2020-2025 German Aerospace Center (DLR-SC)
+* Copyright (C) 2020-2025 MEmilio
 *
 * Authors: Julia Bicker, René Schmieding
 *

diff --git a/cpp/models/hybrid/temporal_hybrid_model.h b/cpp/models/hybrid/temporal_hybrid_model.h
@@ -1,5 +1,5 @@
 /* 
-* Copyright (C) 2020-2025 German Aerospace Center (DLR-SC)
+* Copyright (C) 2020-2025 MEmilio
 *
 * Authors: Julia Bicker, René Schmieding
 *

diff --git a/cpp/models/lct_secir/README.md b/cpp/models/lct_secir/README.md
@@ -1,5 +1,5 @@
 # LCT SECIR model
 
 This directory contains a model implementation based on an ODE formulation using the linear chain trick. 
-To get started, check out the [official documentation](https://memilio.readthedocs.io/en/latest/cpp/models/lctsecir.html) 
+To get started, check out the [official documentation](https://memilio.readthedocs.io/en/latest/cpp/models/lsecir.html) 
 or the [code example](../../examples/lct_secir.cpp).
diff --git a/cpp/models/ode_sir/README.md b/cpp/models/ode_sir/README.md
@@ -2,4 +2,4 @@
 
 This directory contains a model implementation based on an ODE formulation. 
 To get started, check out the [official documentation](https://memilio.readthedocs.io/en/latest/cpp/models/osir.html) 
-or the [code example](../../examples/sde_sir.cpp).
+or the [code example](../../examples/ode_sir.cpp).
diff --git a/cpp/models/sde_sirs/README.md b/cpp/models/sde_sirs/README.md
@@ -3,4 +3,4 @@
 
 This directory contains a model implementation based on an SDE formulation. 
 To get started, check out the [official documentation](https://memilio.readthedocs.io/en/latest/cpp/models/ssirs.html) 
-or the [code example](../../examples/ode_sir.cpp).
+or the [code example](../../examples/sde_sirs.cpp).
diff --git a/cpp/models/smm/README.md b/cpp/models/smm/README.md
@@ -1,5 +1,5 @@
 # Stochastic Metapopulation Model
 
 This directory contains a model implementation based on a stochastic metapopulation model formulation. 
-To get started, check out the [official documentation](https://memilio.readthedocs.io/en/latest/cpp/models/isecir.html) 
+To get started, check out the [official documentation](https://memilio.readthedocs.io/en/latest/cpp/smm.html) 
 or the [code example](../../examples/smm.cpp).
diff --git a/cpp/models/smm/model.cpp b/cpp/models/smm/model.cpp
@@ -1,5 +1,5 @@
 /*
-* Copyright (C) 2020-2025 German Aerospace Center (DLR-SC)
+* Copyright (C) 2020-2025 MEmilio
 *
 * Authors: René Schmieding
 *

diff --git a/cpp/models/smm/model.h b/cpp/models/smm/model.h
@@ -1,5 +1,5 @@
 /*
-* Copyright (C) 2020-2025 German Aerospace Center (DLR-SC)
+* Copyright (C) 2020-2025 MEmilio
 *
 * Authors: René Schmieding, Julia Bicker
 *

diff --git a/cpp/models/smm/parameters.h b/cpp/models/smm/parameters.h
@@ -1,5 +1,5 @@
 /*
-* Copyright (C) 2020-2025 German Aerospace Center (DLR-SC)
+* Copyright (C) 2020-2025 MEmilio
 *
 * Authors: René Schmieding, Julia Bicker
 *

diff --git a/cpp/models/smm/simulation.h b/cpp/models/smm/simulation.h
@@ -1,5 +1,5 @@
 /*
-* Copyright (C) 2020-2025 German Aerospace Center (DLR-SC)
+* Copyright (C) 2020-2025 MEmilio
 *
 * Authors: René Schmieding, Julia Bicker
 *

diff --git a/cpp/tests/test_d_abm_model.cpp b/cpp/tests/test_d_abm_model.cpp
@@ -1,5 +1,5 @@
 /* 
-* Copyright (C) 2020-2024 German Aerospace Center (DLR-SC)
+* Copyright (C) 2020-2025 MEmilio
 *
 * Authors: Julia Bicker
 *

diff --git a/cpp/tests/test_smm_model.cpp b/cpp/tests/test_smm_model.cpp
@@ -1,5 +1,5 @@
 /*
-* Copyright (C) 2020-2024 German Aerospace Center (DLR-SC)
+* Copyright (C) 2020-2025 MEmilio
 *
 * Authors: Julia Bicker
 *

diff --git a/docs/source/_static/custom.css b/docs/source/_static/custom.css
@@ -4,13 +4,13 @@
     white-space: pre;
 }
 
-/* Newline after the last parameter (so the closing bracket is on a new line) 
+/* Newline after the last parameter (so the closing bracket is on a new line)
 dt em.sig-param:last-of-type::after {
     content: "\a";
     white-space: pre;
 }
 
-/* To have blue background of width of the block (instead of width of content) 
+/* To have blue background of width of the block (instead of width of content)
 dl.class > dt:first-of-type {
     display: block !important;
 } */
@@ -86,3 +86,10 @@ dl.class > dt:first-of-type {
   text-align: justify;
   line-height: 1.6;
 }
+
+.page-white-images {
+  background: #fff;
+  color: #111;
+  padding: 1rem;
+  border-radius: 6px;
+}
diff --git a/docs/source/_static/funder/bmftr.jpg b/docs/source/_static/funder/bmftr.jpg
diff --git a/docs/source/citation.rst b/docs/source/citation.rst
@@ -1,17 +1,18 @@
+.. include:: literature.rst
+
 Citing MEmilio
 ===============
-
+    
 If you use MEmilio, please cite our work
 
-- Bicker J, Kerkmann D, Korf S, Ploetzke L, Schmieding R, Wendler A, Zunker H et al. (2025). *MEmilio - a High Performance Modular Epidemics Simulation Software*. Available at `https://github.com/SciCompMod/memilio <https://github.com/SciCompMod/memilio>`_ and `https://elib.dlr.de/213614/ <https://elib.dlr.de/213614/>`_.
+- |MEmilio_citation|
 
 and, in particular, for
 
-- **Ordinary differential equation-based (ODE) and Graph-ODE models**: Zunker H, Schmieding R, Kerkmann D, Schengen A, Diexer S, et al. (2024). *Novel travel time aware metapopulation models and multi-layer waning immunity for late-phase epidemic and endemic scenarios*. *PLOS Computational Biology* 20(12): e1012630. `DOI:10.1371/journal.pcbi.1012630 <https://doi.org/10.1371/journal.pcbi.1012630>`_
-- **Integro-differential equation-based (IDE) models**: Wendler A, Plötzke L, Tritzschak H, Kühn MJ. (2026). *A nonstandard numerical scheme for a novel SECIR integro differential equation-based model with nonexponentially distributed stay times*. *Applied Mathematics and Computation* 509: 129636. `DOI:10.1016/j.amc.2025.129636 <https://doi.org/10.1016/j.amc.2025.129636>`_
-- **Agent-based models (ABMs)**: Kerkmann D, Korf S, Nguyen K, Abele D, Schengen A, et al. (2025). *Agent-based modeling for realistic reproduction of human mobility and contact behavior to evaluate test and isolation strategies in epidemic infectious disease spread*. *Computers in Biology and Medicine* 193: 110269. `DOI:10.1016/j.compbiomed.2025.110269 <https://doi.org/10.1016/j.compbiomed.2025.110269>`_
-- **Hybrid agent-metapopulation-based models**: Bicker J, Schmieding R, Meyer-Hermann M, Kühn MJ. (2025). *Hybrid metapopulation agent-based epidemiological models for efficient insight on the individual scale: A contribution to green computing*. *Infectious Disease Modelling* 10(2): 571-590. `DOI:10.1016/j.idm.2024.12.015 <https://doi.org/10.1016/j.idm.2024.12.015>`_
-- **Graph Neural Networks**: Schmidt A, Zunker H, Heinlein A, Kühn MJ. (2025). *Graph Neural Network Surrogates to leverage Mechanistic Expert Knowledge towards Reliable and Immediate Pandemic Response*. Submitted for publication. `arXiv:2411.06500 <https://arxiv.org/abs/2411.06500>`_
-- **ODE-based models with Linear Chain Trick**: Plötzke L, Wendler A, Schmieding R, Kühn MJ. (2024). *Revisiting the Linear Chain Trick in epidemiological models: Implications of underlying assumptions for numerical solutions*. Accepted for publication. `DOI:10.48550/arXiv.2412.09140 <https://doi.org/10.48550/arXiv.2412.09140>`_
-- **Behavior-based ODE models**: Zunker H, Dönges P, Lenz P, Contreras S, Kühn MJ. (2025). *Risk-mediated dynamic regulation of effective contacts de-synchronizes outbreaks in metapopulation epidemic models*. *Chaos, Solitons & Fractals* 199:116782. `DOI:10.1016/j.chaos.2025.116782 <https://doi.org/10.1016/j.chaos.2025.116782>`_
-
+- **Ordinary differential equation-based (ODE) and Graph-ODE models**: |Novel_travel_time_aware_metapopulation_models|
+- **Integro-differential equation-based (IDE) models**: |A_nonstandard_numerical_scheme|
+- **Agent-based models (ABMs)**: |Agent-based_modeling_for|
+- **Hybrid agent-metapopulation-based models**: |Hybrid_metapopulation_agent-based|
+- **Graph Neural Networks**: |Graph_Neural_Network_Surrogates|
+- **ODE-based models with Linear Chain Trick**: |Revisiting_the_Linear_Chain|
+- **Behavior-based ODE models**: |Risk-mediated_dynamic_regulation|
diff --git a/docs/source/cpp/diffusive_abm.rst b/docs/source/cpp/diffusive_abm.rst
@@ -1,3 +1,5 @@
+.. include:: ../literature.rst
+
 Diffusive agent-based model
 ===========================
 
@@ -148,7 +150,7 @@ To simulate the model from `t0` to `tmax` with given step size `dt`, a **Simulat
 
 For a detailed description and application of the model, see:
 
-- Bicker J, Schmieding R, et al. (2025) Hybrid metapopulation agent-based epidemiological models for efficient insight on the individual scale: A contribution to green computing. Infectious Disease Modelling, Volume 10, Issue 2. https://doi.org/10.1016/j.idm.2024.12.015
+- |Hybrid_metapopulation_agent-based|
 
 Output
 ------

diff --git a/docs/source/cpp/glct.rst b/docs/source/cpp/glct.rst
@@ -11,7 +11,7 @@ An overview of nonstandard but often used data types can be found under :doc:`da
 Infection states
 ----------------
 
-The model contains a list of **InfectionState**s that define particular features of the subpopulations in the particular state.
+The model contains a list of **InfectionState**\s that define particular features of the subpopulations in the particular state.
 
 .. code-block:: RST
 
@@ -20,11 +20,14 @@ The model contains a list of **InfectionState**s that define particular features
     `...`
 
 To make use of the GLCT, we additionally need to define the numbers of subcompartments for each **InfectionState**.
+This is done by creating an **LctInfectionState** object for each group. These objects are then passed as template 
+parameter to the model. 
 
-.. code-block:: RST
-    `Number of subcompartments of State1`
-    `Number of subcompartments of State2`
-    `...`
+.. code-block:: cpp
+
+    using LctStateGroup1 = mio::LctInfectionState<ScalarType, `List of InfectionStates`, `Number of subcompartments of State1`, 
+                                                                                   `Number of subcompartments of State2`, 
+                                                                                   `...`>;
 
 The model is implemented as **CompartmentalModel**.
 

diff --git a/docs/source/cpp/graph_metapop.rst b/docs/source/cpp/graph_metapop.rst
@@ -1,3 +1,5 @@
+.. include:: ../literature.rst
+
 Graph-based metapopulation model
 ================================
 
@@ -31,8 +33,8 @@ Since all regions exchange commuters simultaneously, this scheme offers great pr
 
 For further details, please refer to:
 
-- Kühn MJ, Abele D, Mitra T, Koslow W, Abedi M, et al. (2021). *Assessment of effective mitigation and prediction of the spread of SARS-CoV-2 in Germany using demographic information and spatial resolution*. *Mathematical Biosciences* 108648. `<https://doi.org/10.1016/j.mbs.2021.108648>`_
-- Kühn MJ, Abele D, Binder S, Rack K, Klitz M, et al. (2022). *Regional opening strategies with commuter testing and containment of new SARS-CoV-2 variants in Germany*. *BMC Infectious Diseases* 22(1): 333. `DOI:10.1186/s12879-022-07302-9 <https://doi.org/10.1186/s12879-022-07302-9>`_
+- |Assessment_of_effective_mitigation|
+- |Regional_opening_strategies_with|
 
 **Detailed mobility approach**
 
@@ -45,7 +47,7 @@ Commuters move along these paths and pass through various mobility models during
 
 For further details, please refer to:
 
-- Zunker H, Schmieding R, Kerkmann D, Schengen A, Diexer S, et al. (2024). *Novel travel time aware metapopulation models and multi-layer waning immunity for late-phase epidemic and endemic scenarios*. *PLOS Computational Biology* 20(12): e1012630. `<https://doi.org/10.1371/journal.pcbi.1012630>`_
+- |Novel_travel_time_aware_metapopulation_models|
 
 **Stochastic mobility approach**
 
@@ -60,7 +62,7 @@ This allows for modeling behavioral changes in response to the epidemiological s
 
 The extension and inclusion of regional and global information is based on the following paper:
 
-- Zunker H, Dönges P, Lenz P, Contreras S, Kühn MJ. (2025). *Risk-mediated dynamic regulation of effective contacts de-synchronizes outbreaks in metapopulation epidemic models*. Chaos, Solitons & Fractals. `https://doi.org/10.1016/j.chaos.2025.116782`
+- |Risk-mediated_dynamic_regulation|
 
 
 How to: Set up a graph and run a graph simulation

diff --git a/docs/source/cpp/interfaces.rst b/docs/source/cpp/interfaces.rst
@@ -3,7 +3,7 @@ Extensions
 
 MEmilio provides several extensions to interact with external data structures or software. 
 
-- :doc:The `Systems Biology Markup Language <https://sbml.org/>`_ (`SBML <sbml>`) can be used to semi-automatically create (or load) models in MEmilio from a given model description in SBML format.
+- The :doc:`SBML importer <sbml>` can be used to semi-automatically create (or load) models in MEmilio from a given model description in `Systems Biology Markup Language <https://sbml.org/>`_ (SBML)  format.
 
 **Further advice:**
 

diff --git a/docs/source/cpp/lct.rst b/docs/source/cpp/lct.rst
@@ -11,7 +11,7 @@ An overview of nonstandard but often used data types can be found under :doc:`da
 Infection states
 ----------------
 
-The model contains a list of **InfectionState**s that define particular features of the subpopulations in the particular state.
+The model contains a list of **InfectionState**\s that define particular features of the subpopulations in the particular state.
 
 .. code-block:: RST
 
@@ -20,11 +20,14 @@ The model contains a list of **InfectionState**s that define particular features
     `...`
 
 To make use of the LCT, we additionally need to define the numbers of subcompartments for each **InfectionState**.
+This is done by creating an **LctInfectionState** object for each group. These objects are then passed as template 
+parameter to the model. 
 
-.. code-block:: RST
-    `Number of subcompartments of State1`
-    `Number of subcompartments of State2`
-    `...`
+.. code-block:: cpp
+
+    using LctStateGroup1 = mio::LctInfectionState<ScalarType, `List of InfectionStates`, `Number of subcompartments of State1`, 
+                                                                                         `Number of subcompartments of State2`, 
+                                                                                         `...`>;
 
 The model is implemented as **CompartmentalModel**.
 
@@ -45,7 +48,7 @@ We use different types of parameters to represent epidemiological parameters suc
 compartment or the contact rates between different age groups. Most model parameters are constants that describe 
 pathogen-specific characteristics (possibly resolved by sociodemographic groups) and are represented by a vector with a value for each sociodemographic group. 
 To model different contact rates between different sociodemographic groups, we use a parameter denoted **ContactPatterns** of type **UncertainContactMatrix**. 
-The **UncertainContactMatrix** contains anmarbitrary large set of contact matrices which can represent the different contact locations in the model like 
+The **UncertainContactMatrix** contains an arbitrary large set of contact matrices which can represent the different contact locations in the model like 
 schools, workplaces, or homes. The matrices can be loaded or stored in the particular example.
 In the **ContactPatterns**, each matrix element stores baseline contact rates :math:`c_{i,j}` between sociodemographic group :math:`i` to group :math:`j`. 
 The dimension of the matrix is automatically defined by the model initialization and is reduced to one value if no stratification is used. 

diff --git a/docs/source/cpp/mobility_based_abm.rst b/docs/source/cpp/mobility_based_abm.rst
@@ -1,3 +1,5 @@
+.. include:: ../literature.rst
+
 Agent-based model
 =================
 
@@ -74,7 +76,8 @@ Stochastic Transitions:
 4. **Disease spread**: During interactions, agents can infect each other. The viral shed is used in combination with further personal information and contact details to feed into a stochastic process that determines if the virus is transmitted and a new agent becomes infected. The chosen time step of the model has no impact on the expected amount of transmissions per time.
 
 For details on the mathematical modeling of viral shed and disease spread, we refer to 
-- Kerkmann D, Korf S, Nguyen K, Abele D, Schengen A, et al. (2025). *Agent-based modeling for realistic reproduction of human mobility and contact behavior to evaluate test and isolation strategies in epidemic infectious disease spread*. *Computers in Biology and Medicine* 193: 110269. `DOI:10.1016/j.compbiomed.2025.110269 <https://doi.org/10.1016/j.compbiomed.2025.110269>`_
+
+- |Agent-based_modeling_for|
 
 Data extraction
 ~~~~~~~~~~~~~~~

diff --git a/docs/source/cpp/model_creation.rst b/docs/source/cpp/model_creation.rst
@@ -1,7 +1,7 @@
 Model creation
 ==============
 
-While MEmilio already preimplements many different models, it is possible to create new models. This section describes how to create a new model in MEmilio. All of MEmilio's models have been designed to share a maximum of structure and functionality, however, the creation of a new aggregated model differs fundamentally from the creation of a new inidividual-based model. New metapopulation models are generally created by implementing an aggregated model in a graph structure.
+While MEmilio already preimplements many different models, it is possible to create new models. This section describes how to create a new model in MEmilio. All of MEmilio's models have been designed to share a maximum of structure and functionality, however, the creation of a new aggregated model differs fundamentally from the creation of a new individual-based model. New metapopulation models are generally created by implementing an aggregated model in a graph structure.
 In addition, MEmilio also provides an :doc:`extension<sbml>` to create models from `Systems Biology Markup Language (SBML) <https://sbml.org/>`_ files. 
 
 .. toctree::