Ana R.M. Carvalho

878 total citations
33 papers, 721 citations indexed

About

Ana R.M. Carvalho is a scholar working on Public Health, Environmental and Occupational Health, Modeling and Simulation and Virology. According to data from OpenAlex, Ana R.M. Carvalho has authored 33 papers receiving a total of 721 indexed citations (citations by other indexed papers that have themselves been cited), including 29 papers in Public Health, Environmental and Occupational Health, 24 papers in Modeling and Simulation and 8 papers in Virology. Recurrent topics in Ana R.M. Carvalho's work include Mathematical and Theoretical Epidemiology and Ecology Models (29 papers), Fractional Differential Equations Solutions (17 papers) and COVID-19 epidemiological studies (11 papers). Ana R.M. Carvalho is often cited by papers focused on Mathematical and Theoretical Epidemiology and Ecology Models (29 papers), Fractional Differential Equations Solutions (17 papers) and COVID-19 epidemiological studies (11 papers). Ana R.M. Carvalho collaborates with scholars based in Portugal, Türkiye and Taiwan. Ana R.M. Carvalho's co-authors include Carla M. A. Pinto, Dumitru Bǎleanu, H. M. Srivastava, Natália R. Costa, Adagmar Andriolo and Zoë Matthews and has published in prestigious journals such as Applied Mathematics and Computation, Applied Mathematical Modelling and Mathematical Biosciences.

In The Last Decade

Ana R.M. Carvalho

32 papers receiving 697 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Ana R.M. Carvalho Portugal 14 586 426 177 103 81 33 721
Seham M. Al‐Mekhlafi Yemen 17 736 1.3× 391 0.9× 172 1.0× 190 1.8× 38 0.5× 68 963
Cristiana J. Silva Portugal 15 553 0.9× 552 1.3× 114 0.6× 32 0.3× 36 0.4× 38 858
Hossein Kheiri Iran 13 356 0.6× 220 0.5× 74 0.4× 78 0.8× 42 0.5× 49 643
Nigar Ali Pakistan 14 276 0.5× 206 0.5× 66 0.4× 53 0.5× 23 0.3× 45 393
Muhammad Umer Saleem Pakistan 15 416 0.7× 256 0.6× 75 0.4× 39 0.4× 24 0.3× 59 618
Antonia Vecchio Italy 17 397 0.7× 290 0.7× 275 1.6× 318 3.1× 52 0.6× 77 793
Cruz Vargas‐De‐León Mexico 16 696 1.2× 862 2.0× 66 0.4× 30 0.3× 73 0.9× 69 1.2k
Seda İğret Araz Türkiye 15 869 1.5× 499 1.2× 240 1.4× 151 1.5× 10 0.1× 50 1.0k
C. Rajivganthi India 17 429 0.7× 271 0.6× 242 1.4× 76 0.7× 10 0.1× 39 762
Rahat Zarin Thailand 22 700 1.2× 548 1.3× 119 0.7× 54 0.5× 7 0.1× 57 897

Countries citing papers authored by Ana R.M. Carvalho

Since Specialization
Citations

This map shows the geographic impact of Ana R.M. Carvalho's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Ana R.M. Carvalho with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ana R.M. Carvalho more than expected).

Fields of papers citing papers by Ana R.M. Carvalho

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ana R.M. Carvalho. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Ana R.M. Carvalho. The network helps show where Ana R.M. Carvalho may publish in the future.

Co-authorship network of co-authors of Ana R.M. Carvalho

This figure shows the co-authorship network connecting the top 25 collaborators of Ana R.M. Carvalho. A scholar is included among the top collaborators of Ana R.M. Carvalho based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Ana R.M. Carvalho. Ana R.M. Carvalho is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Carvalho, Ana R.M., et al.. (2019). Maintenance of the latent reservoir by pyroptosis and superinfection in a fractional order HIV transmission model. An International Journal of Optimization and Control Theories & Applications (IJOCTA). 9(3). 69–75. 9 indexed citations
2.
Carvalho, Ana R.M. & Carla M. A. Pinto. (2018). The burden of the HIV viral load and of cell-to-cell spread in HIV/HCV coinfection. IFAC-PapersOnLine. 51(2). 367–372. 4 indexed citations
3.
Pinto, Carla M. A. & Ana R.M. Carvalho. (2018). Diabetes mellitus and TB co-existence: Clinical implications from a fractional order modelling. Applied Mathematical Modelling. 68. 219–243. 31 indexed citations
4.
Carvalho, Ana R.M. & Carla M. A. Pinto. (2018). Non-integer order analysis of the impact of diabetes and resistant strains in a model for TB infection. Communications in Nonlinear Science and Numerical Simulation. 61. 104–126. 41 indexed citations
5.
Pinto, Carla M. A., et al.. (2018). Time-varying pharmacodynamics in a simple non-integer HIV infection model. Mathematical Biosciences. 307. 1–12. 14 indexed citations
6.
Pinto, Carla M. A. & Ana R.M. Carvalho. (2017). The impact of pre-exposure prophylaxis (PrEP) and screening on the dynamics of HIV. Journal of Computational and Applied Mathematics. 339. 231–244. 11 indexed citations
7.
Pinto, Carla M. A. & Ana R.M. Carvalho. (2017). Fractional Dynamics of an Infection Model With Time-Varying Drug Exposure. Journal of Computational and Nonlinear Dynamics. 13(9). 12 indexed citations
8.
Pinto, Carla M. A. & Ana R.M. Carvalho. (2016). A latency fractional order model for HIV dynamics. Journal of Computational and Applied Mathematics. 312. 240–256. 98 indexed citations
9.
Pinto, Carla M. A. & Ana R.M. Carvalho. (2016). The role of synaptic transmission in a HIV model with memory. Applied Mathematics and Computation. 292. 76–95. 40 indexed citations
10.
Carvalho, Ana R.M. & Carla M. A. Pinto. (2016). A delay fractional order model for the co-infection of malaria and HIV/AIDS. International Journal of Dynamics and Control. 5(1). 168–186. 103 indexed citations
11.
Pinto, Carla M. A. & Ana R.M. Carvalho. (2015). Fractional complex-order model for HIV infection with drug resistance during therapy. Journal of Vibration and Control. 22(9). 2222–2239. 41 indexed citations
12.
Pinto, Carla M. A. & Ana R.M. Carvalho. (2015). EFFECTS OF TREATMENT, AWARENESS AND CONDOM USE IN A COINFECTION MODEL FOR HIV AND HCV IN MSM. Journal of Biological Systems. 23(2). 165–193. 6 indexed citations
13.
Pinto, Carla M. A. & Ana R.M. Carvalho. (2015). Effect of drug-resistance in a fractional complex-order model for HIV infection. IFAC-PapersOnLine. 48(1). 188–189. 9 indexed citations
14.
Carvalho, Ana R.M. & Carla M. A. Pinto. (2015). Emergence of drug-resistance in HIV dynamics under distinct HAART regimes. Communications in Nonlinear Science and Numerical Simulation. 30(1-3). 207–226. 18 indexed citations
15.
Carvalho, Ana R.M. & Carla M. A. Pinto. (2015). The effect of noise intensity in a stochastic model for HIV-specific helper cells. IFAC-PapersOnLine. 48(1). 186–187.
16.
Pinto, Carla M. A. & Ana R.M. Carvalho. (2014). New findings on the dynamics of HIV and TB coinfection models. Applied Mathematics and Computation. 242. 36–46. 53 indexed citations
17.
Carvalho, Ana R.M. & Carla M. A. Pinto. (2014). A coinfection model for HIV and HCV. Biosystems. 124. 46–60. 24 indexed citations
18.
Pinto, Carla M. A. & Ana R.M. Carvalho. (2014). Strange patterns in one ring of Chen oscillators coupled to a ‘buffer’ cell. Journal of Vibration and Control. 22(14). 3267–3295. 1 indexed citations
19.
Pinto, Carla M. A. & Ana R.M. Carvalho. (2014). Fractional dynamics of a model for HIV and TB coinfection. 49. 1–5. 3 indexed citations
20.
Pinto, Carla M. A. & Ana R.M. Carvalho. (2013). Mathematical model for HIV dynamics in HIV-specific helper cells. Communications in Nonlinear Science and Numerical Simulation. 19(3). 693–701. 9 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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